{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "85c84540-074e-4b8a-943c-e993f3d100de",
   "metadata": {},
   "source": [
    "# Fourier features to capture seasonality"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6c7e22b9-366f-4754-ba9c-c642f5b6f291",
   "metadata": {},
   "source": [
    "[Feature Engineering for Time Series Forecasting](https://www.trainindata.com/p/feature-engineering-for-forecasting)\n",
    "\n",
    "In this notebook we will show how to create fourier features and how we can add them to our forecasting pipeline."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "9a86e7d9-212c-4d82-b896-20a4e078c336",
   "metadata": {},
   "outputs": [],
   "source": [
    "import datetime\n",
    "import re\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "\n",
    "sns.set_context(\"talk\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6e964ccb-f3fd-4e88-a08a-b82e6fc56074",
   "metadata": {},
   "source": [
    "# Data set synopsis\n",
    "\n",
    "We will use the Victoria electricity demand dataset found here: \n",
    "https://github.com/tidyverts/tsibbledata/tree/master/data-raw/vic_elec. This dataset is used in the [original MSTL paper [1]](https://arxiv.org/pdf/2107.13462.pdf). It is the total electricity demand at a half hourly granularity for the state of Victora in Australia from 2002 to the start of 2015. A more detailed description of the dataset can be found [here](https://rdrr.io/cran/tsibbledata/man/vic_elec.html). \n",
    "\n",
    "We resampled the dataset to hourly in the 4th data preparation notebook in the \"01-Create-Datasets\" folder in this repo. For instructions on how to download, prepare, and store the dataset, refer to notebook number 4, in the folder \"01-Create-Datasets\" from this repo.\n",
    "\n",
    "## References\n",
    "[1] [K. Bandura, R.J. Hyndman, and C. Bergmeir (2021)\n",
    "    MSTL: A Seasonal-Trend Decomposition Algorithm for Time Series with Multiple\n",
    "    Seasonal Patterns. arXiv preprint arXiv:2107.13462.](https://arxiv.org/pdf/2107.13462.pdf)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "9a8af020-f4e4-4bce-8dea-e4e7d57819a6",
   "metadata": {},
   "outputs": [],
   "source": [
    "data = pd.read_csv(\n",
    "    \"../Datasets/victoria_electricity_demand.csv\",\n",
    "    usecols=[\"demand\", \"date_time\"],\n",
    "    parse_dates=[\"date_time\"],\n",
    "    index_col=[\"date_time\"],\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "7a1c7c23-5218-4da0-91bb-c94c68859c26",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(115368, 1)"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e60cdf1a-6461-4fb3-ba03-ba6227195790",
   "metadata": {},
   "source": [
    "The data is relatively large compared to the other datasets we have been working with. If the rest of this notebook runs too slowly on your laptop try filtering to a recent segment of the data. For example by running:\n",
    "\n",
    "```Python\n",
    "# Filter to the previous 3 years of the dataset\n",
    "data = data.loc[\"2012\":]\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ea3cc441-df77-439b-a88d-e74c334635c3",
   "metadata": {},
   "source": [
    "## Plot the data"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6263c527-b50a-4998-a4aa-79b05ed40cc2",
   "metadata": {},
   "source": [
    "There time series is high frequency and over a long period. Let's plot the previous three years."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "e096e012-faba-477d-b0b3-6d2a2aac6407",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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1PCHEdwB8CcDbijz7Z6yP7dKOB3A8gEFZ5XKG55C+JxcYjl0IoALAaIPcVQCGAThPCNHXq/yEEEIIIYQQQvKDa88XNGEmhBBCfFGsQf4uyfzvpGCeAaAOQJMQYrgQ4vOW9JMy/y80HpRSVgDYakjP5l0kcx1yzQewH9KKbhNCiFrVH4ADNNdHCCGEEEIIISSPUL9MCCGE+CNuFxmeEUL0BvA7APOllKWW5CYArwGYCqABwHcB/B3Ad4UQJ0kpqzP5Ds/8v92miu0AjjB8PxxpP812+ZDJu9rbVRBCCCGEEEIIyQ8M8kcIIYRESdEpmAH8FMBhAB6yJkgp3wPwnuHQSCHEdKSD9P0D6eB/ALBX5v82m/JbAext+L6XIp+xLKMcBzqLn7ZwBq2YCSGEEEIIIYQQQgghRU4xusi4BEASwFA3maWUnwBYg7RiOktL5v89bE7Z05CezeuUD5a8hBBCCCGEEEIKCBomE0IIIdFSVApmIcReAM4HMFFKudPDqVsAHGT4nnVvcbhN3sORDupnzOuUD5a8hBBCCCGEEEIKCMb4I4QQQqKlqBTMAM5BOrCeU3A/J74IoMrwfUnm/5ONmYQQRwA40pCezfttIYSwlPldAI0ArH6gCSGEEEIIIYQUGbR0JoQQQvxRbArmiwE0AxhplyiEONTm2MUAjgEwLntMSrkSabcZ12SCBma5FkAKwAjDseFIB/I711DmIQAuAjBaStnh92IIIYQQQgghhESLW8WxpA0zIYQQ4ovYg/wJIe7MfPxq5v9LhRCnAqiVUg405DsIwFkARkgpGx2Kmy2EWARgMYB6AN8B8CcA6wA8Zcl7C4APAIwTQgwF8HUANwAYJKVcZ8g3HMBcAG8IIR4FUA3gOqSV8/d4v2JCCCGEEEIIIYUGLZgJIYQQf8SuYAZwv+X7FZn/NwEYaDh+EYC+AIYoyhoK4GwAvwCwN4BtmTLulVLWGTNKKT8SQvwGwN0AnkHahcYDVnmklEkhxC8BPALgRgB7AZgP4DIpJd1jEEIIIYQQQkgBQ8tkQgghJFpiVzBLKa2+jZ3yDQIwSJPnTgB3qvJY8o8CMMpFvt0Arsr8EUIIIYQQQgjpZtCCmRBCCPGHo4JZCPF5PwVKKTf7F4cQQgghhBBCCAkPKo4JIYSQaFFZMJcDvvYS9dZnIYQQQnoe1Y1t+Pu7S3Dm1z+DS7/3hbjFIYQQQgghhBBCAqNSMN+HXAXzOQBOBDABwKrMsa8B+CmAJQA+DFc8QgghpPvw4MerMbO0GjNLq6lgziN3jFyOZVvr8O4138M+e8TuHYwQQkiecWvBLGnqTAghhPjCcZYlpbzH+F0IcTGAowF8W0q5xJL2LQCTAKwLX0RCCCGke7Btd0vcIvRI3p6X9t71xpxNuPa0Y2KWhhBCSL5hkD9CCCEkWnp5yHsbgIFW5TIASCkXA3gWwO0hyUUIIYQQEhijNVpLeyJGSQghhBQ6VEMTQggh/vCiYD4WQKUifWcmDyGEEEJsKBYLqlEl23Dd24tQ29wetyiB4W5nQggh7l1kRCsHIYQQ0l3xomDeDuA3QghhTRBC9AJwAYAdYQlGCCGEdDeKZeL696FL8MnyHRgwZk3cogSmSG45IYSQAqBYFoIJIYSQQsOLgvklAKcBGCeE+IUQ4ujM31kAxgH4IYAXI5CREEII6RYU27S1rLopbhECw4BNhBBC3MIugxBCCPGHl1DqAwAcBuBvAH5qk/6slLJ/KFIRQgghJHZy9ywVHymjsqA7XBAhhBBCCCGEFBiuFcwybQL0dyHEcwDOBfDFTNJGAB9IKddGIB8hhBBCYkKg+BWy3O5MCCHEtQ/maMUghBBCui1eLJgBAFLKdQAeiUAWQgghpFtTbO4aenlxpFWgGG958avLCSGE+IGLjYQQQki0dIOpIyGEEEKioFtYMBsVzCFdTmtHMpyCCCGkm1Ld2IZnp5Ri867muEXxRJGtAxNCCCEFgycFsxDiFCHE20KI+UKIDUKIjZa/DVEJSgghhBQ7xTZv7Q4ui8O2Wlu8eTe+ce943P/RqlDLJYSQ7sTfhpTgkXFr8atnZsQtCgAqjgkhhJCoca1gFkJcBmAmgAsA7AlgM4BNlr/NEchICCGEdAt6ygS3PZGKW4ROwr7nN71bgvZECq/MLAu3YEII6UbM2bgLANDQmohZEkIIIYTkAy8+mO8AsBbAGVLKiojkISEjpURrRwp79esdtyiEENLjKTb9svBhwnzr8KX4ZPkOjL7hBzjm0H0jkMobKYOGuTu4/CCEEOKdYut/CSGEkGLDi4uMLwB4nsrl4uLeD1fhm/eOx6JNNXGLQgghpMjwo44dtnArGtsSuHv0ytDl8UPYSgUqqQkhhBBCCCHEjBcF81YAe0QlCImGwbPL0Z5M4dq3FsctCiGEkCKjVwBdaluiMALhhe0iI8g9IYQQEg+yp/ioIoQQQmLCi4L5BQCXCCHoa6EISXFQRQgh8VNkbbEfFxlZUoVyqRHK0dpRGEp0QgghhBBCCIkTLwrmRQBaAcwXQlwhhDhdCPEj619EcpLA0OSKEEKIN7pDz2HywRzCBRn11ecOnEWrOEIIKQLYUhNCCCHR4iXI3yTD55eR20+LzDFaOOeR56duwJgV2/Hyn07Gp/fb0zFfGJNqQgghwSi2CW536DuM9zzsy1m7swEpCfTuBveJEEK6M1wLJIQQQqLFi4L58sikIL7539g1ANLB/J69+FuO+Tj3JYSQ+CmGCa7ZItd/71Eo/U7YFsbW4tLlF8rVEkIICUYRdNSEEEJIAeJawSylfD1KQUgwdta1KtO7gxUaIYSQ6EmmwnUpETdGX9BRXA9VEYQQUgyE31o/Om4tNlY34unfn4Q+vb14niSEEELStCWSmF26Cycf9Snst2ffuMUJBHtCQgghJE/IIlBHRulSIg7CvufW8orBKp0QQohb7Hu+prYEPlxagbqWDgDpIK8Dp5Tik+U7MLJkG1IFE9mWEEJIMfG/MWtx+eAFuOr1hXGLEhgvLjIAAEKIwwCcDOBTsFFQSynfCEEu4hGdVZboFmoCQgghUWNUmHaL6XKIF9HQ2oEtNS2W4rvFXSKEkG6N+8VA+4z/GrYUY1fuwLc+fyDev+4HSBgUyk9OXI/7PlqFF/74bfzgS4cEF5YQQkiP4dVZZQCAeWU1MUsSHNcKZiFELwDPArgKastnKpgJIYQQG8Kwdq1ubMOn9u6H3r2iWTgMS2FaKO41zC4y7IV6b+EWLN9Wh7vOPh59Fducbx2+LOcYLZgJIaT7M3blDgDA4s21OWnbatMLj5e8PA/lA36VT7EIIYTEyIptdZi8phJXnno09tnDs/1ut8OLi4ybAfwFwDsA/oT0/qHbAFwPYD2AhQB+FraAxB20UCaEkO7P4s27cfIDE3HZq/Miq6OQFaa7m9oxe0O1p63IOoW5lBK3DF+GN+ZswvuLtyrzjlmxw3W9hBBCCoewuzbOvAghhJz9zEw8PmEd+o9ZHbcoBYEXBfOfAIyVUl4GYEzm2CIp5QsAvg3gkMz/JA44yiGEkIInqPL2f2PWAABmle4KQZri42dPTMPFL83D2/M3uz5Hd887kl0ZrO4vwiifEEJI/LCtJoQQEhVT1lTFLUJB4EXB/EUAYzOfU5n/+wKAlLIJwGtIu88gMVAs+uX61g7sqGuNWwxCCImFoPPbPr3z29oX2oS8urEdAPDazDLX5+guwWjh7MetB30wE0JI98Ftv8eWnxBCCDHjRcHcAqAj87kR6X7104b0HQA+F5JcxCOF4utSRTIl8Y17xuN7/Sdh6+7muMUhhJCio1ceGnvz5LpAp9AeboPRnYbd7QuqRC80JTwhhJBcZMiNddjlEUIIIcWOFwXzJgDHAICUsgNAKYBfGNLPALDTS+VCiMOFEAOEEFOEEA1CCCmEOM0mX3kmzfo3wCbvgUKIF4UQVUKIJiHEZCHEiQ71nyOEWCyEaBVCbBZC3C2EyPHM7aXMuLDzwTx8kdqXZL5pak90fh5LP5aEkB5IMUxIe5pFrvEn8aO+71l3ixBCujdu13HZ9hNCCMlSDHO8fOAlzOFkAOcjHewPAN4EcJ8Q4gik52Q/BPCox/qPA/BvpJXVywB8X5F3EYAnLcdWGL8IIXoB+BjACRlZdgG4DsBUIcS3pZQbDHnPAjAqc11/y5zzX6R9Sf/NT5mFxs3vLY1bBBN85wghJBj5aEeLoa32ogjWXU8q4AVzQEkIIYWP25batYuMlD4PIYQQ0pPwomB+FMB4IcQeUso2AP2RdpHxRwBJAC8CuNtj/YsAHCKl3CWEOA/ASEXerVLKtzTlXYi0kvp8KeUoABBCDAOwLiPbZZbrKQFwppQymclbD+B2IcTTUsr1PsokKoxWYsXg04MQQnog3U1dalQg2+32MV2vj76pu90vQgghenrabh9CCCHOsEdI49pFhpRyu5RyXEa5DCllUkp5o5TyICnloVLKa6WUnqK3SSkbpJS73OYXQuwhhNhbkeVCABUARhvqqAIwDMB5Qoi+mXKOB3A8gEFZ5XKG55C+Jxd4LTNuik1fW2TiEkJIKAT295uH4UtYFrl2ytyw8LJIqbua4BbMZj/PhBBCCo+wN5tw8wohhJAs7BPSePHBHDc/B9AEoEkIsUEIcY1NnpMALJK5s+P5APYD8CVDPgBYaMwkpawAsNWQ7qXMToQQtao/AAfoLtYrurk2V9kJIaT4yffgpVAHS95cZKgvIvA1SuBv75YELIQQQkiUhD0XKtDukRBCSAwUm8FnVHhxkQEAEEIcC+BYAAfDZo4npXwjBLmsLAMwA2m3FIcCuBrAICHEQVJKY6C/w5H2qWxle+b/IwCszuQzHrfmPcJHmbESpaUYIYSQcCiGxT7p8LlYSZncM+Wmh2Gx/fEyu+EEIYSQ7gr97xNCCMkSdEdkd8G1glkIcTiA1wH8NHvIJpsEELqCWUp5jkWW1wDMBHCXEOJ5KWVdJmkvAG02RbQa0o3/O+U1uuFwW6ZR3gNt8ncShRWzbsUkagV0U1sCe/frrdy2XAyKFUIIKWQY5M8P7i2Y/fSU7NsIIaQICNtFRrjFEUIIKWJ21tupDHseXlxkvAjgdABPIu2j+HSbv5+ELJ8tGb/JTyKtCD7FkNQCYA+bU/Y0pBv/d8rbYvjutsy8o1o5z+eq+vyyGnzz3vG498NVrs+pauQLSAjpeRSDD+bQqnDQ1q7eXo9B0zaguT3hv2gPmmCdAjkMH8yEEEK6H6r5FK3VCCGEEDNeXGT8BMBTUsqboxLGI1sy/x9kOLYdXe4vjGSPVRjyZY9b97UeDmC2jzLzjmpck88xzw1DFiORkhg8uxz3nPM1VzI9P3UDfvKVT+P/jjrIMT8hhBAzebFgjliJfdZTMwAA2+talX2GCi+7cnRXY0z34z8t7LtVWd+Kg/bphz69iylMBiGEFDZu22rXbTr1y4QQQogJL7OXRgClUQnigy9m/q8yHFsC4Nsi10/Dd2GWf0nm/5ONmYQQRwA40pDupcy8Y1w5t4qXz1V1txNyq0SPjlsbuiyEEFLIFNt8NMrdMBNW7YysbCPmvlKd7ocw79H8shp856FJuPileaGVSQghxB9KY578iUEIIaTA+fpn949bhILAi4L5IwBnRCWIE0KIg4QQvSzH9gRwC4AGAHMMScORDrp3riHvIQAuAjBaStkBAFLKlQDWALhGCNHbcP61AFIARngt0w/3fLAS93640u/p5sBFlrR8Dnp6udQwWyfxHJgRQnoaxRAUyCiiV2kL8fq0Ipn6Uu8mzGFe8cNj1wAA5pfXhFgqIYSQsLunAuzuCCGExIRbnVh3x4uLjH8BmCSEeALAMwDKZAgzSSHEnZmPX838f6kQ4lQAtVLKgQDOAXCHEGI4gHIABwP4E4AvA7hWStloKG44gLkA3hBCPAqgGsB1SCvS77FUfQuADwCME0IMBfB1ADcAGCSlXOezTNekZNqlBABc+O0j8bUjvMf8U1llubHIaksk0dyWxKf26ee5biNuX6YckTgwI4QQT+Sj2QxSR8rDyUGGEH59MNvhRWY/5XuBg1NCSFwkUxJXvb4A++/VF0/+7kRl4O6egqp5Z4BXQgghWbjomMa1gllKWSuEeB3AEwBuBHLdMqSzSS9KawC43/L9isz/mwAMBLAcaWvjSwEcCqANwGIA/5JSfmSpPCmE+CWARzIy7gVgPoDLpJSllrwfCSF+A+BupBXmVQAesMrjpUwvGB/AhlZ/gY5UgYvcPOBnPD4NW2paMOu2n+CzB+7lSwYvWAdiHJgRQnoaxlZPSul9Ap8PH8yWDqSlPYnXZpfh1C8dgm8ceaCnc5V5/QjnA9NirI2FsrEvUv0c78zfbHs8zL6M+hxCSFzMWF+FKWvTngdv/OmxOObQfWOWKFz8tNXpPs2+YaYygRBCCDHjWhkshLgVQH8AO5FWsO4OQwAppXI6JaVcBODXHsrbDeCqzJ8u7ygAo8Is0w9+ByiqgZKuTCklttS0AADenb8Z//r5cf6EgAeFAgdihBDSiZTeFYr5WJiz1vDExHV4cfpGPIy1KB/wK0/nKvMGuJQ1OxqwaVcTvnDwPv4LyeDWgvn295fbJ9CCmRDSDWhPpDo/t7QnY5QkGsJWCOcz3g0hhJD42bq7GXePXonff+fz+Nnxh8UtTkHixdr4bwCmAvhFEL/DJBe/CgOTD2bLpFRXZtAtwea63GGt04+vS0IIKWoC+DfOFyYfzBKYtrbKObPiXB1BdamXD16Ayf86TZvPtNvHpk5psnD2TqH+joQQ4oU+vbtawESYE4U8MmfDrlDLU7rIKM5bRAghxCc3vbsEizbtxqQ1lVqjm0Jh/c4GXDRoDgb+4Vs49dhDIq/PS5C/gwAMo3I5fPxaLKUUk2LduDCZCjah9gNdYhBCSBd+fBDne87vtTpVvxQ2G6uaXOXTWZnpFNA6wlQysJ8khMSFyvVesfCHl+Y6poXZui7fWhdiaYQQQoqBdTsb4hbBMz97Yjpqmzvwx1fm5aU+LwrmpQA+H5UgPRm/gzjZtZMtZ1KsU1ykgs6ofZAjUrGOXgkhxCdBJrgbqxqxaFMo3qmU5EvJmb/FTU160CB/VAoTQroZ9NaTxql/uPqNhbRgJoSQHkYhd42tHUmc9+ws/GvY0ljl8KJgvgPANUKIk6MSpqfiN0qz2SpLWNLMea0T4HxamXXJYKZXIb+hhBASAcbFP69z0ztGrghXGCcCTJq9uciIphOYsb4K5w6ciQXlNRmZ3C+4+pGJSgZCSHfAbMHc/QbpbncNuclX19LBxUVCCCEFw/BFW7FkSy1GLN6KprZEbHJ48cF8KYBtAOYKIeYA2AjAGgFCSimvDEs4okY5rPHgIiOwHC6LSlnq7I6DV0IIcYtXxWRLR36CLlnF8jKJLoQJ96WvzAcAXPTCHJQP+JXegjlgfWFeMZXVhJC4MJmtcIgOwLlPS0nJ9poQQkhgSivDcbthDM6bNZ6pbmwLpWwveFEw/9nw+QeZPysSABXMHnl0/FoMveZ7ni2nzCvszhbKdqQU7jXyBQevhJCehrnVLszZqTnInzcZzcFnQxIoIFJjoazrLwkhhBQ/flr612aVI5mSuP70L+WUxb6DEEJ6FtZ5hJ94OlbOfHJG4DIA87wrK9WVry8MpWwvuHaRIaXs5eKvd5TCdlfml9VgQ1Wj5/OUkY0155pdZATTArhVkljfv9kbdmFVRX2gugkhpFjxOibJ11T2hWkbfJ/rZaCVDwX0i9M3aO9zYB/MVDIQQroBxdiWSSnxj6FLcMfI5S4yey9/wJg1eGTcWizdUms6LvwVRwghpIhRzV38Gg6F6VkgS7Y7t/Zd+cCLD2YSIQ2t3v2kqMaBulX1ZAyDSDuZLs1TNEtCCCkEAjW9eWi3WzuSGDy73Pf5hTbhfuiTNS6C/BktnL3XUYQ6GUIIyaEYXWTM2bALI0u24e15m30Z67hlR32r6bsQbPsJIaSnU0j9QFSxbbziWcEshNhHCHGGEOISIcRhUQjVE/GzcNGocN6te9iN/pDz9SzaibSrqT0/lRNCSAFQqG4xsrjd8lvV0Ib5ZTU5Fm/egvx5kcw/pv7OJr2QfpFCkoUQQgqd+taOzs9tHSlFznD733RfxxabEEJ6MgXbC8QomCcFsxDiWqQD/Y0H8AaAr2WOf1oI0SqEuDp8EXsK3p+C0x+d6lyaBwvmoHN8Y1XvzN/sWyZCCOlJFGKTaHWZ5LQa/oMBk/HbQXMwbuUO03Hpwf1SvgK96qzygrqMKsTfkRBCvFKMbZlR5igXLe3uTTHeL0IIIf7YVtuC2uYO07FC0m8Zu8A4YwS4VjALIS4A8CyAKQCuguEapJSVAMYCOC9k+XoMwX1AWr5r8rcnulb5wxyQ3f6+sw+0wnn9CCEkHkwB9Dy2inG1oXb9U3sy3YcMmb9Fm9eJvO2eidoHc5i/DDtKQkhshBefJV8Yd4D20nQqYc63JdhcE0JIT+KaN3ID5hVqPxCnXF4smG8BMEVKeT6A0TbpCwF8PRSpeiBeXWToVktUqxZSSvz8ieneKlTJ4jZfAa3wkMIlFYGje0IKEc9B/qwLiRG0qda+Q1dHImnekhz327vbxu2S8RrsLifoKn8UwTkIISTf5MsaOEyMC3y98imzjNdCrLy6CSu21cVWPyGE9DRWVtTnHDMZDhXQdKAoLJgBnABgpCJ9O4BPBxOn5+L1IQhikZWSQFtC7acsCgrppSOFyb+GLcX3+k9CpSWYCiHdBeOkPWiTGEWb6rVIldJbp6CIQhdw3nOzco5Jh8+dxwLexzMenxasAAOF7qObENIzKBYFc8qDUjxYW597clzzmtaOJE57dCrOfmYmNkYY2JAQFTvqWnH/R6uwdkdD3KIQEhuFOm6PU+/mRcGc1OQ/AkBTMHF6Ll4fAp1CWpWeSOVfuQxEa9n20bIKTFlTGWENJB+MWLwVlQ1teGLiurhFISRyCnFXh1eZrBN6L2dHEe14067mnGNm6wK1ksBJJGMgKSs0YCaEkHgwL2qG06fYN+nCkkfGNoHf3dy1U2deWU08QqAwxzAkf1z9xkK8MrMMZz4Z3q5oQoqNQm0G41R8e1EwLwVwpl2CEKIXgIsALAhDqJ6I105aN6FVFWfdzhu2/2cnojLVX7OjHjcMKcHlgxegxmZ7NCk+jJHApZT465uL8Nc3F3EwS4oesw9mj+dazojibbCW6XXC7skHs6eS/eM0yNpe14KOZMrVIOyMx8KzUlbBJo4QEhfF2PwY20ytD+YA9fz1rUU59cY1gTctisYiAfDyjI34vwcnYemW2pgkIHGznC5aCCkopOOX/OJFwTwQwFlCiPsBHJQ9XwhxHID3AHwNwNMhy9dj8GoBpVPW5m5b7vqcsCqYvVXtm6gmzqWVXdvDqhvboqmE5BXj812ypRZjV+7A2JU7sKQbDGTX7mhAS3sybjFINyCKBZcwA94VyhZrY5eXvb45G3bhlP6T8dtBc1z1v5UN7Ft6Oos27calr8zrFv0QIXYUqi9JFcbxoq7LCbvPjOseGauNq5994OPVqG5sw1U2Qa8IIaSnUKh9ZVCx1u5owOBZZWjt8K6z6OM2o5RyqBDiBAB3ALg9c3gs0v25AHCPlHKMZwkIAO+r4DkKZBfl1Ta34+KX5uFrR+xvOh7cstjd+VG9gEaLhTgdmvdEWjuSmLKmEt/74sH41D79QivXqPAxNmytHfG4dwmLsSu2469vLcYXD9kHk28+LW5xSAyYfDAHDfIXXBybSlwd6iRncuvJR4aHvAGwUyo8Nn4tAKBkc615i3V+RHKEPVjhcsHzswEAM9ZXo3zAr2KWhpDwMc4dimU4HbacUkrUNju7RCoEzH1WvL1WU1si1voJIaRQKKR+M6gsWdc32+tbcftZX/V0rhcLZkgp7wRwMoCnAIwBMB5py+bvSCnv81RzD8f6m4dtwWxX3jOTS7Fqez3eW7TVLEueXoaotpIZo0bH5F66x3LfR6tw7duL8fsX54ZabqFYPnqluT2B12eXo6za3h39wCmlAICNDumkh1FAA5EsQdvpAtQvY/nWrm2c2esz9qG6IICEENITKKTJsVuM40Xt7k4X5b06q9xVvdJFfVFhqjbm8XKRDteJB1IpiSHzNqNk8+681mt16UlIIVKwQf4CyDVo2obOz58s3+75fNcWzFmklIsBLPZcE1HidZCiy21nsVXfYr8iH1SZ51b0qMZhxv6nl6clExKUIfM2AwDW7mzA9roWHH7AXr7LKnehdN1R3+K7/Hzw0Cer8dbc9D2xs3ArxskbiY7AytwInievZVqtp8y+IcOdevrd3vzYhK6godkiCvVVpJ95QkghUKiTZhX6uZG+jPs/WuWuLukc5K+5PYG9+3meYvsibgVvFMF6SWExYvFW/GfkcgBdc5vRS7aZ8mypacbnDto7tDrnl9XgisELcP3pX8K1px0TWrmEhE0hDduNc4ggcvUfs6bzc0fCe0Ge1XFCiH2EEIcLIfbxXBtxJg8WzHE//1G9gFEqNIh7Tuk/2fe5ze0JnPboVG2+fwxdivU7G3zXEzWjSyqU6YXUCZF4MLZRY1bs8HRurouM8B8ou75FpfRUzS118kUZQFCHnV9mQoxEoexvT6TwxIR1mLm+OvSyCQmKaTdHEbaLeplD9sHscPzRcescUkKq1zjviVnBS/1y92f2hl05x256d4np+w8fnqItZ8zy7Xhp+kZXfeufX5uPxrYE/jd2jTYvIXFSqF2lk1znDpyJ/p+sdl1Oe9K7ewBXCmYhxBeFEC8KIbYCqAewFUC9EGKrEOIFIcRRnmsmJjz7YNb+1nZKAk9VhE5U1hBGhUgvDnQCM3N9Ncau8L4dwi/N7Ql8897xpmOqn3Hogi3RCuSRprYENu2iywviDmM7ePv7yz2ea/kehQVz4PPdl+C1uQ5jO7IEUNPUbol8XzjDQ7OCp3Dk6glMX1eFv765CFt3N6OhtQOnPToVf31zUah1vDKzDE9NWo8/vjLP87ntiRSem1qK+WU1AIBHx63FTx6bih11raHKSEjxonGREWKTKuHcRs/ZmFbINbR2RBLU2RRMN/TSvRF3/SQ6Khta8dL0jdhZH7yPaUskce3bi/HgJ6sxdW2Vi/z0eUmKg0IdqzvJtXRrHQZN3xi4HBXa/TtCiNMBjAKwH4A2ACuQVjLvD+DLAK4B8DshxDlSyhmeJSC+8GfBHM0L4LbUqFwpmVyRcaQTiPrWjs6J78c3noqvHXFA5HV+uLQCHUmFhWSBD19//MhUVDe24f3rvq/MN2/jLqzaXp8nqUh3JB+DmKBVeDnfa3sdxtVLCfz1rUU5xwoRKdmn5ZPLXp0PAJi8thLtmcntpl3NSCRT6NM7HP9bQXxYvjKzDA+PTQenLB/wq06f/vd/vArPXvytUOTTUd/agY5ECgfvu0de6iP5pVAnym7RzTPCvDopncvrSKbQ3J7ADwZMRp/evTDn9p9gjz69Q607S9x9RNwW1CQ6LntlPtbscL9rtL61A/vv2dc2rd2gMC6tbMTpX/m063Lz6XKGEK8Uaq+p686llJG138oRsxDiAADvIH3vrgZwgJTym1LKH0opvwngAKQVzALAu0KI/SORkuRgVTBbB4XWh6qyoc3Rx23egvxFVJEpmjIHOoGobery071mu3dXFLub2j2fY/dYFNPvWN3YBgD4zXOz0aCIpv27kAMhEhIFdguRXlpuc+yhsH0w5x7burvZczlZC9DOcv0KFDFxBZDq6bTbWE4lfGwRtCNI1za/rGub8gdLu9wxNbQ69zth0p5I4Rv3jMe3H5iIkx+Y2Nn3ke5JMTY/+gl1fuqTUmLuxl2ob02gpqkdq32Mp5X1Gj7HPVyOu34SjIbWDows2Zozf6usb/WkXAaAk+6b4Gqu7/WZ+cmj07ydQEgeKdS+Mt/9oRGdScZlAD4N4NdSyleklKbWR0rZLqV8GcC5AD4D4NJoxCRWrKv01mfEbmK6eHNtJLK4VRxH9RwX6otdjBg7fT+39aT7J6AtEf52QCNWuTqSqc5nsL61AzPXV/tSBry/eCt+/cxMrCtgH8+k+AlT6RpJ2xfYgtmLiwyPPphthDvrSW8bp3Q7eQqpPykgUbodXratSwDbLW4oVlbU+VpQDYLxebjxnZLOz35alBnrq/D4+LWe+utttV1Bdqsb2/DouLU+aibFQnEG+dO07y6uyZvyy748CaC3Iep4MuQtnCbDmph3+VG/XNzc/N5S/GPoUvzptfmm4z9/crrnspIp58CXVlZsq8NvX5iDaevs3WUYn6sdIbjoICQyCrSr1PV3bo1Y/Bj96RTMvwAwWef6Qko5DcBUAL/0LAHxRZiT5HytPkcW5M9wLwpJOVDs+LWeq6w3WzUlkinc88FKDPPgO3lkyTZsqdFbJja1JfCjh6fgohfmYHdTO75xz3j88ZV5eHpyqWe5/zlsKZZvq8PVbyxU5mvt8KZAn76uCvd+uFKZZ93OBtw2YhlKKxs9lU16NlEoAAL7YI6wDbYrW7VrwG0ZhdRvGGUpJLm6E1PWVuKEe8ah/yerXS2ISAn0tgR4+NXTM/GdhyYGkmP0km2Bzg/Cpa/Mx9OTS/HyjDLfZeTLcprkj2Jvf1Ia24Kwr8lRbyytuyvDrddI3BbExbTjsDshpcQbc8oxY73en7GKcSt3AgCWba0zHa9t7rDLrpfL5fELX5iN+eU1+NOr823zE1IsFOpirNaCOcK6dQrmryOtOHbDlEx+4gOvgx5d/kLbWptKSdz30SrbtClrKwOVbb7UwrruYsM0TvR5K0eVmCfN7y3aisGzy3HriGWYXVrtWtH8lzcXobEtgdveX2Y6/srMsk7l8/sl27C9rhULN+3GSfdP6Mzz9KT1/oRH2uemExNX7cQJ94zDoGkbXJd32avz8dqscmWes5+eiXcXbMFZT3m3GCDFRZgDkUiC/NmVqahHNbnUzTs9+2COapGywPrLLIU6aC12Ln9tARIpiUHTN+KGISXa/Ckp0cvmYVXFDrBj0abdnZN5ALjp3SW4+KW5gd1vBHlKlpiCXZKeTjG2OeaddzoL5nBxdJFh+R62CraQfiUGV4+HsSt24L+jV+LSVwpLQetW/9DawSB+pPtRSG2zThbru9rakcS5z87Cv4cvczjDPToF80EAKjR5slQAODiYOD0Xr/Nb60Oxs76wfeGNWbEDSx0mMpe/tiBQ2cZbEVUgwZ6C6bHyOWh8bMI6k4/T8l1dvr8vfnkebh2xDFNdLCqs2l6PEYu22ip8b35vaUbeaH7wd+Zvtj1+1RsL0ZGU6D9mTaj1tWcUDB1Jif6frA61bNJ9sD7u0XjI8FaqtZlwE1TCL3EHqs03Bar37lZ8vHy7Nk91Y1soSpQ/v5arCJi9YZfJn7KKgnseqFjq1hTa4+aGKPsfL+VJGa2qvrDaAjYE+cDqzmjZtjqHnPHi7JfcWzk0jCfFQmG1x13o+jtr8pB5m7F0Sy2GLjQbAvp5FXUK5n0AuHV80wZgLx8yEHgfyFkVqau315u2W+bTgtlNTX4CMfmpv1Bf8kJlzoZdOP+5WZi3cVdOmkD6ubr0lXl4YdoGNLS63y61QjPwcesPfFVFve3xnRH747r9/eWRlq9i0PSNsdVNoiff/hKb2hKYsqbStWsXa9/iVVq9zy9D2R5nEFEtIC7evDuagn3ALiztOuKU/pMwc3113KIAAH43aC56haBhbnJw57Lb51bkMJiwaicGjFmTMxHZursZHy/brrau5sPa7TC7yOiZP7CXN13pDiBAX+el5rhdVFARGD2jl2zD1+8eh7fnbeo8ZuyS7MYwE1ftRP8xq9GWSGL9zgac8fg0vDmnXFnPPR+o3fm5wUn/0FPbE9L9KdQnWyeX9ZV0GqMmfby7OgUzULj3rVvhVSGcsplp3/Tuks7P+WzHc6zqbCpXDUA+vd8egeo33rti3N7nlsa2BO4ctRwTV+3UZ3bJH16ai5LNtfjdi3MBmH/LXkLgd4PmYMb6agwYswYn3DNeqzh2S9LgKE/1bOgGrm6f89rmdlTUtqChtQPT1lWhPcGtWaT4cTNgv/btxbh88AL8x+WiibVMry1qpBbMIXRsdmU8PLYrWFkh9SE9dT5207tLsL2uFX98ZV7cogBIB7eLUocS98T7hWkbMG7lDtOxU/83BdcPWYxXZ3X5aKYeqXvR2pE0BW4EirPNMS7a6uZSYV+fW2vNsN8d00JtyGV7Je76ewI3vbsEHUmJO0au6Dxm3Pnyr2FLc8656o2FGDRtI16eUYbrhyxGaWUj7hqtViAPnl0emsxWjM9sTQgBclMpiVml1aGURUgQ4h7DOaH3wexuvlfb3JEzVtDhRsE8QAixTPcH4CFPNQMQQhwuhBgghJgihGgQQkghxGmWPAcLIW4RQswQQlQJIWqFEHOEEBfZlPfnTBl2f3va5D9HCLFYCNEqhNgshLhbCNHHJt+BQogXM/U3CSEmCyFO9Hq9KsLwwdy3t/tBVpC6wy4vsFWayeIiYFkFzCNj1+CtuZtxlSYIXRCa2rtWr4QA6i1BfM5+ZqbnMset2KHP5EAYlhHJlMSp/5uC7w+YjF8/MxN/enU+Hhu/Vn9ihmenlOLqNxZi9XZ7a+oo8NqQk+JgR10rNrsIXumE28GAkemZCN3vl7gLKBZ0G6N2xdxb8aGd21mGVgEeQiVB6CELpt2Fj5a59SIXHEdryRAe2nKH2AMjFjm3Gx8v347ZG6oLdnJF1Jz55HT8YMBkLNta23nMtCMw7xL5w0ugbzdtqpfrdipPZv5FhXGOF7cFcdz191S21HTNE5KKifTKijrsasyfEtaNBbNdTAMr1t1+uy2K5LfnbcIlL8/DGY9P8yElIeFhfOJXb6+3NQLNmyymqtVyLN1ShycmrHO1Q/2Rsd5cg+oUzJsBpADs5+IvlcnvheMA/BvAkQCcPEqfAuBBALsAPADgDgAtAIYJIe5yOOcOAJda/kwtkxDiLACjANQA+Fvm838BPGHJ1wvAxwB+D+AZALcCOAzAVCHEMW4vVI9HC2abBnzPvr19luafKWsqUddifjDt6lYN+oJOTkwWzMUyIvbB8jz42zr/uVmdn8Oy8nWauAJAIpnCkPnugv55JRuIr7EtgcbMto+sLG7dUEgp8ci4tZiwaifOempGJHLa8YMBkzvfi0QyhdLKBtfvybKttSitbIxSPOKTv761KND5ubtFAhUXQA7nio1pG2yewyAyyzxsPNhS04zJa3YWhNKsAEQoWmqbw51QO/0UNwwpwa5GdzEw4t7KruK9hfb9sFFJZif+xS/Nw2Pj10UlFomQbHyLl2eU2aYXY/vjdUtwKiVx4zsluGvUCvsTPJbXVa45LexX37AJMO9ut6zEXT9RG5V9snyHaxdpbhjm0FdkcXwnTDtkzWlbXBhenHT/BNO8NBs8nRbMJG6sz7zVh3Fc8wldtX94aS6emrQe93+0Sps/4VFprlQwSymPklIe7eXPU+3AIgCHSCmPBfCIQ56VAI6VUp4npXxKSvksgJ8CmAzgdiGEnd/nT6SUb1n+rFPTRwGUADhTSvmSlPJGAP0BXCeEONaQ70IA3wdwmZTyvkz9pyE9jrnb4/U64tmC2ebYXgYFsxeCDHwuH5wboM+uo1NdXogGzN3a4svPlaVSEpt2Nblq3Eo27zZF9e1w8L144fOzlavlXhgyf7Nj8Meg9B+zBu2JVKDV7TgnWL97cS6klLhp6BKc8fh0x0mgkbLqJpwzcBbOeHwaWtrDG1CScFgS9rMewfNpt7XXWo1p4qwQqaKuFet2NiCRTOHZKaWYub46UBsdRvuuK+HdBVtwxeCFeG/R1sB1+aEYLQjDoqK2JZR3ZPSSbTjxvgn4n0eLCxWqPq+2JZgP5aD9jJ3iOpmSmF1ajcfHr8XyrXWmMYDdbpwNVU1IpiQufH42Lnl5ric5B04p9Sc4KQgUy4V5lCIcvAY1mrWhGh8srcCbczdhkyEgtfv63KWFrYSlBTMxoutDmkKcD9w6fBkqFXFwjM9mY1sCr8wsQ2llA3734pzO49aYBj98eEpuQTbPVWVDV73GS652uchLSBRY5yavZVyLSSlxxeAF+MWTM0Jd5HEvlzumrq3S5nGz68CU31PukJFSNkgpc6OLmfOUSSk3WY5JpC2O9wJwlN15Qoj9M9bHdmnHAzgewCAppfEXfw7pe3KB4diFACoAjDbUXwVgGIDzhBB9VfK7xeswzm4QZbJgjnFcaFe3Sp6gAQnNQUkCFVXQ+Lm2295fhh8/MhWvzNQrJx/6ZLXpu9Nq1cJNuzGrVB18yW07pG/U1AXp3FbM3lCNqgb/A484H6f5ZTXYtCsdaAkAHvxktXbytKC8pvMzB1zED26UuObJrfodnbtxF95ZsAWPjFuLP74yT6mc1soWwgvptoyRi925FImSQrCiDpu5G3fh2SmlaE+kcqyMvz9gMs57dpbDmXqWba3Fc1NLO+NRPD91Q04eJ/dDO+rUgWOzrmbsCPozuV048fI8/G7QHFz88jw8PbkUvx44E09PSiuBm9sTjrtx5m7clenflcNy0s0wPlfF2OaYfTCr81qTGw1u4Jp9KOGslmqd9UQUL6Arretz3Ppdr4oHEhzrsxGW0Y9bVIuqRknu/WAl7v9oFc54fDo2VnUt4Ng9MwPGrMEzk9Z3fveyi/bkBya6zkuKh7LqJlz1+gLl+KsgcNhdWt3YjslrKrF2ZwM+WJI/d2pWOVznD1HrEauCOSCfyfxvp+maAaAOQJMQYrgQ4vOW9JMy/5uc2UopKwBsNaRn8y6SuT39fKRdg3zJWnnGT7TjH4ADrOeEYcG8Z99emhz5wU5hrFIiBx2HBVVQd2eGLUxb4T3w8WpNTmBB+W7T9y8cvLdjXifr5iwLLWX5RTdufXeBZqtWwPrzMdl6fILz9mJr7XdqtnFyoN+9ybEkjqCdz3HD4UIO1fmplMSykCy3i6ml99t2mBZMQ5KlkPj9i3PxyLi1+MljU3HifRPw3FS19esL03KVxE6cM3CWKWCjHRe/lGudu2JbHcqq1daLrQUQGHbGevuFXbtnbeEmcx/8xMR0P6PaTmzXr0e5zZ8UBk5tTnEOrXUWzOZ0oyWln7nEh0vtlQbSIonXd6e2uR2n/m8Krnvb3q2WznUN6d7kjLPy/LKqrDGNoox2eD/seGHaBjw2YZ0ymHxxtknEL1e9vgATV1fislfnxy2KEqfH0thOt2n0JlHgdo6Y7UOUO3I81l2UCmYhxEEArgIwNWNNnKUJwGsArgfwGwBPATgbwCwhxCGGfIdn/t9uU/x2AEdY8jrlgyWve3Im8d5+OruHwKhcKrRGWDXZDmzBbPi8Ko+B2PJJKiVNgVj84NWncp9ezs2D7if7ePl2TFq9U1uHXyVM+a5mrUIgDHRGAVnfzn7I+hx72rBir+Pteblu7nfWt+LlGRtR3dhmsmThwkv3J4qf2FahbKlIXa/FskaG1zeF8Uy7thY1BY7yXu+oJd4toJvaEiZf+935Fd66O21JrFMIDxjT5ebi6Unrcd6zswL5XNxkExPg7GdmojWhtl708wxU1La48i0Z9u/8+uxyx7ThCtcvhewjmkSI8Wcv8gUufZA/M8a+KevXOIy3QEpg8pqdpu9eGLpgC7bVtuCT5TvQZtM2mcem9hKXVjZgoWFXW1Sw2YiGwbPK8PDYNRhZkttmW8dClQ1trvoaI09PWo9T/zfZl2zzy5yfKzd9pSpLlWL3ZYnCWCGfAXdJfthQFf08PwwKdayecqn2cSO/1zFw0SmYM24v3kbaCvhGY5qU8j0p5RVSyjeklCOllLchrWg+EsA/DFmzfpvtWrFWQ3o2r1M+WPJm5ThQ9Qegzvozed/dolml91pciNhbMDvnD7y91FDArcOXmXw0dReemVzq4xkxc8OQxZ7yq5Q5z7jwufhORMH7slxiY4lmJZHU37QJq3Y6Trp1yqgnFdbHOn748JRQLKR//+JcPPDxalz5+kLTQL9QOzzinxxFbwR1uFHimlxkWNLsLJhNytogPpjz6CLDiJ+296XpZZ7PuffDleYDPegddtMWPj5hHZZsqcWj49diY1UjLn1lHiau0i9kuqGm0b/S2s69RmNbAt8fMBk/fHhKZxDAfOhhSisbcPcHK23T5m3chScnul/QJD2bYhxDaEXO2cqcawkcxmXvqG81jYHrW735aTcqvhtacw0ZdD6YO5IpnPH4dFz4whytK7nuTGVDa2gBy/NJbXM77vlwFZ6bugH/GLo0J93uGf2TSyvP7DP/+IR1nQu9XlHtlsw+mlHc+xvfKcHaHQ2Zesx34YYhJSjPg+ERsSeZkrjlvaUYOLnnjTHucRhzxY1n41WfaXYUnYIZwDMAzgRwuZRyuS6zlPITAGuQDgyYJdui7mFzyp6G9Gxep3yw5PWNV0WTzs9xMflgDqpks56+fmdjoPIKkez2ViufLN+OP7w411WnOn7VTtuVcCdUv8rSLbVIheDzK0gJFRqfmQDwwMerlOm1ze24+o2FuPm93AEcoH5udze1o7Qq2LMWhtu0rCX30i21ZmucYpwdEhM1Te3YutvZKiUKFy52Qf48nW/5npQytL4pn0FcjXL6eZf8BPSwLnR156C1Vry0hbub2nHDkBLMWF+Nq95YqD/BBf36qIfDqkfgj6/Myzm2obKrb1gacPeRF3bWO1t/6XZ42b3rPecJ7LmYDZiL+xfXjUut15evq73k5Xlo8KhkzmI/p3Je5AXSu2GyzNkQrU/1QrVgXlVRj+88OAnnDJwZtyhaapra8eHSis7g3LqgfHbPxEaXytWr37B3u+IF1W+ejflz2SvRuDVQxQDyqzAnwfloWQXeW7QVj45fh+Z2/7t7i5GxK3eYvmffD1Nw1xjm5J6rVLqz7cYWzEKIuwFcB+BWKeU7Hk7dAuAgw/ese4vDbfIejnRQP2Nep3yw5M0b2kAWHh6EsJ95rz6YgyjZ6po7cqx1CnWw48Tcjbvwz2FLtEGG7Lju7cWYs3EXrn3bnXXyP4Yu1Qbo60Tzu7xfotsCHmybFBDc4stuO7SR3c3qAb8qcMaPH5mi9Xmsew+d/Pep+MfQJbjng5XYbHNtJgtmzyWTOHB6RjqSKXzr/gk49X9TUJEJTJaf3zS3FuMRaVEY5+S1WjBLaWrjjcle2+pR2jZHj9t7aMznR8HsJ2CUtZZCXSN6dkopzn5mhjKSvFe83OMxK3aE7g6rb+9gbXlOfsPnjsxOGqfAuYs37/ZUtoogfabufSzU55EEQzi4MAp7AfOd+bkuvsJGJ3Gcz/Bsn4peO6W/sSmxc21jTO8V8ZyoUGN/PJ/x379mRwOWb3X26xs3k1bvxLfun4C/vVPi2hLSqb98ZNwa2+NGJrpwX6hzyaj6zQdOKcWKbXVYk7E0DpswjWekTFvd3vLe0k7lPvFHpWFxO99BJ3W0JZJ5DWCbVSyb2m6P7WSFQ0BqHcY6X5qx0eO5zrh1t5GlaBTMQojrAdwD4Akp5aMeT/8iAKOv5iWZ/0+21HEE0u40lljyflvk9uDfBdAIQO8rwAVhR3qM89W2q1v50AZ46Z+clGvZ27tABztO/P7FuXh/8Tbc+E6J7zK8bAu65OV5rqyPdc/Yok3+fbtNWVOFRDKlfU7j/ilVAabqWxPagfXkNZXK9JUV3ge9I0u2YfDscvzoka6t16R4cXoVjX5mp6y1f46iaOd1zfGq7fXKAEPWdsPqIiNIe//QJ/rJU2gEtLpu8WHBHHfgHrc8Mm4tVmyrdxU81i0Feqm+SRgCuvzlzUXYqVDGj1sZzM3HjPXVXZMnRZekX9DNPdk4KetmPxHREPbvffv72k2ngfHqgzmfWK36ZpVWY6mLALh212Qcw9u98sa+o1fEGuZimHH9euBMz25K8sWVr3ftwhm6MJhrwWenpOcsXv0xG7n3w5Xa51L3SPlVjrkhrHFHS3sS//fgRLy3aCveW7QVX/3v2FAXzXsa5nlB4bQK1Y1t+O5Dk/Dn1xbkrc7svQgyrv3xI1MCyzF6SQXW7XS/0KMO8heRBbMQYp0Q4t9CiM94qiEEhBC/A/A00r6X/6XId6jNsYsBHANgXPaYlHIl0m4zrhFC9DZkvxZACsAIw7HhSAfyO9dQ5iEALgIwWkoZSo8VRpA/L+lGsu1AKiXx0vSNmL6uSn2CBmmzyqFaOQoy4LML9hP1YCoqSrb4t2Ly2panpMQGjXsHr6tVuTgLtWp7fec2qkJlflkNBmp8TfdWtKBbaprxyfIdzhkQ3PJjGaMtFz1uVtU7FT+WrPkK8mfkV0/PVAYYylWSmgu16x/yisubFlQp7sdFRq4Mhc3uZv9+i62o7nEQa5jZLnfshKmYqm1ux4UvzDEd0wVz7TAopJdvrcP2Om8T9MqG4IuNdt3Rhqqmzt1V+bQAItHi5GIhzF94qsPCaNh48fGveoSj1okYx9RrdzTgkpfn4dxnZ2m3k9sqmDWGcSYFc8QXVkjKpCyplESJZWfITh+7RONC19bqmuL+Y/wrYV+bVe642yZL0Hl2MvgEM3Bb9eqsMlRbYi94tfgkXRTq8OCl6RtR29yBaQF1W17I3gtVvBodHS5iSLmhysXY0E1NXn9fLxbMHQD6A9gshBglhDg7E3AvEEKIO4UQdyKtsAWASzPHbsikfwfAGwB2AZgE4BIhxB8Nf4cZipsthHhXCHGrEOKvQohXAbwJYB2ApyxV3wLgWwDGCSGuFkI8BeA/AAZJKY1mscMBzAXwhhDiv0KI6wBMRfre3eP3utstUYE9WzBrJ0PeH8wPl1XgwU9W4zKXgQLc1l3T1I5nJjsr6oJMWuxeWONgKpFM4c5Ry/HmnHLfdXRHJOwDh1jzKNO1P5s6wxtzNsU6YZVSKhv83w6agz6aQZRq4P73oUv0WxODjsstt8840K9rKUxrDWLGaRxv63cx53v4748bH/rKBUNLUjJlljLp850Pq61wW4rxd/Gj3zQqDP1SqAP2KFBda5D+++KXc/0j+0H3DDS2JVBR24J7P1yJ/4zMtdTUnf/67HJU1LbguDvH4NcDZ+KU/pM9yZdVwttZIWfx+zhdMXhBoPNJ4eGm3wna/uTLYsyLnDk+mPP4UPcyzJiNyk+7sZpugdO0s8DWwtlQb9QK5khL98ers8py/PFuUcSziIsnHeLr6NAtercnon2wgz5TbRGNj4zvTU1TO/7w4lxHYyY7a+UC8+xQVBhvXSEtRkftrsPuWrPvp24hMBp57GVRkRVNNaf0ehddK4illF8D8H0ArwM4HcBoAFuEEA8KIY7xWK+R+zN/F2e+X5H5fnPm+/EA+gE4FEBWYWz8+6qhrKEAvoK0ovjpjJwDAZwipTSZ+kkpPwLwGwAHIx048DcAHgBwoyVfEsAvAQzLpD2CtLuN06WUvt1jWBcmvD7/dg/B2p0NnT6E/ERuNfqoChLAzXrqw2PV25qDtEN2K+e9DVq99xdvw1tzN+Ou0SsLqsGzQzUxDJuUlFrladT3S0qp3UYV5T257yN1AEBAb5mhGmSt3l6vHYQF9eGs4reD5ugzkdhx6tBVbiiixI3SWpUjdwIvTc+xcbDjZeAX1iDRrb/blIPMbglD3GIPuGVl6AJnH6yqezxsofvgtHHx7vzNuGLwArw2q9xh54r6t5y8phL/HrEMbT7GbgAwbqV6twyg7k8OP2BPx7Ssv+sCH0IRD5gsq0yxG9xbAxcKpudSZ3yTk260MIu2ozWO94xi6Oq1uyTdJRsXclU77fyy3rjtugA1zI+Nz1XcXjF4YWdQ7ELhyYnqnS1OqB7zj5ZVBPa7HbVtTBhB4u0wvt+PjFuDORt34X6HuZ6dBK/MLMM2H+49NlY1YtiCLb50L90F0+JkRHWUVTf5ci0ZJXaPcqcFcwGsWHgRwUt8HR2euh0p5Vwp5dVIB7i7CkAZgNsBrBNCTBZCXCyE2MNjmcLh76hM+mBFHiGlnGoo604p5YlSygOllP2klEdLKW+SUto6i5VSjpJSniSl3FNK+Tkp5d1SyhyzTinlbinlVVLKQ6SU+0gpT5dSuouq5v4+eMxvf/yGIYshpQxsORDE96P1WjZrfEGFWZeVrYYV60JzOp+DQ4/t5tnwYwGvVW4GrNONTBuq4hvsvTarXJtHO8hSZGhuTwbeRqYLQpgjj+FzwT/vBIDze2I87vgURfATu3lvjW4ucnwwWy2YpVlNYWzv1+xocB3c1K/ls5VZpe4CLZkCE8Y1ZyjwV7isuimnf3pv4RbcPXpFjgV3XUsH/j3C2QerahwQ1Br89veXBTof0PfDyZQMFNRISuRY3K32EMjw3g/Tk2i/i1FSulEaON+DZzQuQEhh4fS+eVHWFgpeRFalR72Q6xRMUVevnZLC+PvZtU1JgxVTFC4sfvbE9NDLDIJ1IdtpcWTsCv1CXFh0JFNoT6TQlkhixbY6PPjxKlfb1QH9OEzVX94wpCTwsxzEuMbN+Tvqne/Dmu3hBAfcqagDcL7Ht7y31HNdP3lsGm4dsQzfHzAJdR7nbd0F0+JkBGPmtkQSpz86Fb96eqbWxadZrmix3WGS/d80jyvAlbgM7u6Rtzvpa11TStkspXxNSnkq0hbD7wI4DWmL4gohxJNCiM/7Kbun4vUFcGoYJ62pRGOb2vWBE8YJfBDdlNdzw64r6bAnQedTKm7smp5Hxq3ByQ9MzDl+16gVgeqS0rxdzz6P+n65sW4J6oc0EYKfrijRWygHK9/qQ86KXwujVRX1GLN8u6eFrfZEquB3ARQjjgpmw+fsY2a9/9ZTpZQYVbIt0Aq/mwU/1XNnPT+ZMl+j9ZV+dVaZO7ny3BQ4WV3nVYZYanXP1t0teHPuJgDp+/XXNxfhluHL8PqcTXh3vtlaWRehXdU9r690P5mw4535W0LxiZ1vznpqhmuFRFAk9Bpm1Wvw2AR/W71JPDgtYBZbH1/b3I6bDQohrfjWPjSPl2scD5p2KGnO0/lgtrsE49i5u7vISKUkfjtoDs56aobWgjRfVvl1zR04pf8kfPnOMfjxw1Nx9jMz8dKMMtz0bkko5Uf93OrmLkEfqQ+XVjim/W/sGt9B5O8yLG5r3yuHZ6E8gJV7dWM7/hbSb1xsmC2Yw39AGw1uPWd48KdsdvsUvlwqF0ZxzB2C1Kg616sKzffGGSFEbyHE+QAeB/C7jFxTkPZXfAOA1UKIc/2W3+PwaoEaop8UO1P+II2D9dwoXzC7kqW5Nen8WAwWnUu31JoCfjw7ZQN22QQyfHPupkAT5oWbaly4Z1CXoUsXAnhCMel082skQnJyHxW9A/hoBvQDIF35Ojbtsh8o/fLpGbj27cWYvMZdEJ7KhlZ896GJuPqNRYHkIbk4usgwBYewfw6s7+DoJRX4+9Al+NXTM/3L48aC2UE5kUpJnDNwliWvswUz4N6dkxsLZp0S0wsmpXhcCuYCbP5qLYH9/jt6JQBgyZZajDW4aSirNu9cUo0pXp6xMQ8umdTpuuGBtj/0Jo5DHbmleIkADkSr7CnAx5H4xNGC2eFzoTLQEt9FG+RPkRa1BfOs0l2d8yzT7bepV6esMVsw555vnO9EHfc87iB/pVWNWFC+G2t2NGCKJrBkvvrU9xZt6Qwgt8Pg63f2Bnc7qLRorqNkc22g4nW7L6NetBixeJs2j917sWlXM97KLHprz3e4h0F3y03PYzC5QsJslBFtXX53B0fx/tu2v5mDxmcprmbSy9haldXrPMizglkI8RUhxCMAtgEYAeBkAI8C+LKU8gwp5a+QtmpeC+Bhr+X3VLwqdMP0k5IlqRmwuMV6bpQNjd0DbxxY6Vb5C4m2RArnPjsLv3lutudzvTZcl74yX+tnKuj9SqYkJq7e6ZjuxqL8vUWF7XtTd991CmLdHfA6iLNm1ymQZ6yvzpXJstUQAJ6fugG7mzuUv2cx0NSWwBaNy55848k/Vs538xHd5CosnPx37rAJmpJMSaU/Y7cLf27y/f6lua7KcoNpAh9aqd4oNB+oiWQKJ943wTbNr+9gAHjg49WRT0iCDu6jXmQI67dWBXcNOm4sxAUP4g/zRj971w3F8HvXt5qfd6+GEVKRFjbvzN+M4ZkxrZeq7H18qpcCzD6Yu7kFs3F8EZMh0ZtzN+Gsp2Zgo4et+35Zvb1e2x/ZGSZ5QTf30D1TQcfZOqWYKn5P1gJZ63qmCNq3YiJ6S+Guz17aHF3A1KCoyjQbCsWDmyuuamjDim3qna9eb51rBbMQ4kohxCwAKwH8E8BSABcBOFJKeZuUckOXELIU6SB7QYL/9Sg8+9D1neiM0c1hmArmSC2TFCtHQPBATXHg1o9j0MvR+bkKarGlUyAXgkV5pWb7sW6AsrVGraQPasGsmxcEtTLPzS9x5esL8cunZ5os6QshUEEY/PiRqfjhw1MKKkiE2/Zxdmk1Nu1SD9rDeKfsxMkJ3Odwrt2Og0RKmk6wurpw67rIzTO4dEutq7Jc1UcL5hxUysug6AK+BkVKoLrRv7uJ/mOiC1bsplw3z/bmXc245k1/u0zciF8ICx4bqhrx+uxyU/9EvGPsK0y7UFz4sS1kdBLnuJnKs0L9nWygU7OJshK7MUJKM19LROyD2UjMBswmrn17sWs3ka0dydDmp3eNWoHV2+vx96FLQilvjsLS+aynZrgwTglW/3gXQWNVVAXoawH9u3jfh6sc83Q1bfkJZL9sa20o5URN1PM49ZKXd0YvMVuxvzh9g0NONR6aWl+obquDx9a8cudIdy5VL35pbqjeEbxYML8E4GgAAwAcI6U8U0o5wi4oXoZVSPtkJi7w+sOpGkbP1tAAmtsTeMfgMzFQ4D1D/SWbd2NB+W7fZXmpK4tx4JXK8+CxmNBFltZtE1INgIB0gAvVwLYQFMz/CDgYnF+u9hMWNHq3bmJg9U36wRKzXzPde2xtRxrbEpi8phKrt9d3Wtp0J7IKprfmbtbkzB9Or4F1C+3FL89T50E4ilA3/YfTpNyu/rZEylSmtV1JunSuHFaQP7eYAgbF1FTF30L6Rxf80coHCp+MYSAhlQt+USvT3CwG2mUpy7g5+tNr87V1uPVn7lR/GHmmrK3E67PLIzMs+Olj03D3BysxQKPwJ2pMv4/RN7Dh8KWvzC/4gFVeDVpUqflQqPfLDAq9KGPsxgi6HTbG8XXvyH0wx6thXrfTPA5+dkqpc2yLTMKKbXX45r3jcUfAeDZWKjWB5exksePWEerAtLrnvCOge8Epa9VuHnTvSlAF91RN/XUtHTlBcbNk3w2dDE5zUK9TU6tbuELkg6UV+Oa945W+r92ydXezrUFA2G7lbnp3ien7SzO6xjd+F83sxFq0qQbb6/wbONg9R9l6YvHBbKlSt1s9S32remHO65jOi/rjNwA+J6W8Q0pZrssspZwvpbzckzQ9GK8PoXKQ5F1bjYfHrjUduundJb5Xu4yn/eZ57+4ePNVlo5twsmAu6tm6DXY+2BLJFGqa2lHX0qHd7qAbFOp+f12jlUhKZQ2FYBWru4agA2etn2vN+bo+dJfFSmD8KrMLiyB9WzEGxXJP/M9eJy5EcXoMrKdGZcGcW6/ROspZHrsyrTKGacEcJmEPlv3JEF29r8wsw4XPz0ZlQ5dbkzDr81pU1AuOUqq39RbqAvRdo1bgOw9ORK0LRZ+uv9ApBXT93WJd0FkpcflrC3D3BysxcXW07no+XrY90vK7O+btxsJw3PyMvDjDn9VYXOgtmK3587uQ2K9Pr5y69P2LjQLD+NnmdGO/GrUP5jhZt7MBN75TYjq208ZVl5Vbhi9DWyKFIfOCGxsY5xFe9F5Bnreg3WXUMQ+C+mi2c7dmRB1oOv2/UYQ1O+pz8jkZLVQ1tBXE/DRMbnynBA1tCfzN8q54ZXdTO0793xR8f8DkXPdExt8k4tvn9/GytrWzN1Tjgufn4JT+k33LonqXjDoq1fhqZEmBGHSF+Lt5UTCfg7S/ZVuEEN8RQrwaXKSeifet7Io0r3UDOb5VJ67eiZmluf5ZXZWXEe4HAyZHPmCzG5hlj7V2JPHi9I1dckXY4sXRGU0y+Ndt6UhiR10rvnznGHzr/gn45r3jtdvpddwZcGW/Q3NPdIqlX57wmUD1FwJ+AxFk0U34deWHuXBV7BTqgNHuN2pPpPC7QXM6vzut1lsHNmFcol0ROSI61GP/vEmlbzbXPpjzrAE0u1fKa9WdRHnJ93+0Cgs37cYDH60GkLYIOv3Rqfi7QwT09kTK04Jxa8K8QKWbEHQk/ftwdnN+yslEOEPQWx10fKG6PzpXTm7ZWGUf9DWL7hru0Gy1ND6vugVuN7S0J/HUxPVYtClXsV1I2/KLEbdjA7dBWOMi5znQXFbco4BOC2bNDhnjIbv+x9je2b23piB/IWuYrX14nO+iV1cOWdGN19D/k9WBZPjBgC7llJc+2ynrQs3OyPS5wZ7koGML3flRu2VRj8lyE3/x5IwcoxnVNazanquQtq2pUFemI2KZoV9fbwlAbF40i1YOt8ZfW2qaMXh2uWP6h0uDL1SrXWSYVnId+cfQpYHlyBKkbQjTeNWLgvnPUPtUPhrAn7xVT7J4NzpWrd55VCpJ+wfHujplxcmfYbYst2b5QbC70qwi6ZnJ683HI2rw7hi5HP/34MS8Bw+rtKzwPj5hrekat9UGk8etHzMnEsmUcuCpUxjFHZk6LUOw8zdrngld8doggj4EVLrXMSQ99MkaWz+XUQ+oHvhoFf72TkmoFo1SSvz+xfACwIWJ3VVOWLUTFXVd77ejBbPl5DCU6G5+X2dLZRtLK2ke8FhFdGvBrHsewn4uTRP8Al2cCIOsBfNrs8pQvqsZo5ZU4Pq3F+fczzErtntatBwyb7PW4tXIG3PcRX6348mJ6/DeQrUFiO4X1Ll80hF0t0vKYRwWpgzvLtiiSFVX/poL9xthvyVPTFyHJyauwwU2CxutHSkMW7glL+PMYmT8yh1K36BOgVqtz2DfoH6+IkZlkWyf3934Jyr62rjI0LsyM39vakvghiFqS8SEwXTOTcvUlnC/Y60Q3NupULWDj01Yh/rWDtP8YpDBECkfzFifdv/g9Cxe+MIc2+MmAv4EjQF92OsegajdsvgZ71ljSKieY7vid9a3YmTJVpOiusBfhbwiTZ+jvTFuH6/7Plpl+m79XcPo3tRB/oKXXygkUxJDF2x27XM8zJHDPgAK21lXIROjiwwJ6UopvauxDac/OhV3j05bsZz/nL3foYcCrgZ7wa6TyXYak9dUafOGwdvzNmNXUzse/Nj7dT81cb0+kwPWLUjDLBPsuCcGOosy7SC1GzTMxx++vzJd10kGVUDrrFFz0i0HnplcmnN+lAOqLTXNeHlmGT5cWoEJFncfQUikpMVfdvyLF1ns2l6rpYWbwVRVQ5tpV4N/efR5zIvyxu3V9nlVLjLctss6V81hP5cF4YM5j/W2dnTd4I+Xb8+JndDS7t1lzt8NPvSCXot1QdXIkxPXY+tutfJbptSTHmMMCj8EtyiT2kX9KNH9Pvd+uEqdAeG7kpm9oWsX3e6mdlNaY1sCtw5fhjMemxZqnd2BORt24Zo3F+GcgbMc21enn8r6G8Y9jtRhvYwgu0Hz4QrJzkWGrlqrXKMswa/szjf2s7qrGlmyFV+/e5zrNtBqHBKnMYhd3TpxHh6b6789rPnhjvpWbVmXvpL2px+kxqDjnRenBVOqPz81d25gJOpHQnX97Yl0onWhIe2bu+tEr7vifvX0DPxj6FKTxXtc7tOCUN/agUTAHWO25HHXn9vHq8liKGf9vVS7K92iegZMC7m+SvdOkEdSdQ/mbNyFf49Y7trnuHLkIIT4vBDiR0KIH2UOfSX73fJ3HoBrAahbHOKIdwtmVZp3C2Y7K7I+lm1VT09aj7LqJryesTTaUmNvOTJmxQ5s9uieYfIaf8oku0t1cvDv552TUuKeD1bisfFrsWJbHV6dWea40u9ni+8TE9f5kCpNn97q5ko3MXhWM0AISkITZEKnYP54efw+FoN2CHv17R3o/HbNM+XHz5nxrgukA3H+YMBkDJm3OUdJsjqzTcy0Mm156doSSTw3tRSLNum39el4bVZ55+cai0IhCLnPWuEMClVtmA6jRcYtw8PaYmVvhWzOYS/f9HW5gVmkJbfR569d2U7oJgNhW1V5sTDzwva6Flz1+kKMXaHf2humFUhVQxt+9vg09B9jXgh1urSWAvPB/vC4tcr0rOLGCWlx1ZJv9EokuPKzHBVh3Jqw76+xf/tu/0m2eQrtOS0E5m7sssZ3ahbdTnx171XcxOle0A92Fsy6a7CmW8fWz07JHcubFMyaCv4xdCk6khK3v79cLUgG62Lv6u31sQSDrGvuwCMO/YLqildvb8h55r0+Ry3tSfz93RJbpfxTk9a7UroHGVcEHRsE3fmxQeNuKU4TjhGL7XczvTFnE96a27VTSrUzze7+Vjem5ySvG3ZbFbo1vx3fvHe87a4gNxh/15wdlCEoa93idu6bE2zakm6W2Z8sqvPiCfJXGM+kbuRwOYCpAKYg/bvckfls/XsfwEkA/heVoN0d74Mk1YqJ9/rtGsnevcyPR4MmwqRZBm9CXDF4oaf8qnqyOjnrJfl551ZW1GPw7HI8M7kUZz8zE/d9tArPT/Uf9MSPFZgTuga2n0bBHPVktiOVij26dNzoFgF0z+R/R69Upuvurhvl5Z9enY9ttS34z8jluYpECdQ2t5u2r1uLfG1WOR4euxYXPO9iW5+GLQYrxE016gGsF6ztW9AAJGHi5FbCiJO4Fxm2Us4vC67gt6vb7hG1e67W7WzAAza7ONIWzF0n/Pm1BdqyPlhagX8OW4IGg0WnbiA/YEyuVVIgIrJsu3X4MkxcvRN/fWuRNm+Yc5dHx63F+spGDJq2Ef8ctqTz+LyyGjS3J/RbyzXlB32jrj9d5YENaNSMP7QKZhmtAinoIxLGMxa4WQsoQtjbYo2XU+i+gPNNZX0r/vTqfLy3UOX2xLnddGpbrIf7asYwcWN95rTKWmt+07nRT8y7LJgNCmDNoq61bbB+X7PD7AsVsCqYfYnqiN1i78Ap/ndj+uXt+f7dKlnbSq/t78szNmLUkgpbpfyTLnemWl02eKGtI1h7GPVbHbbfbytufi+7wH53GeZUXl1kBMlXSEgJLN0aPEZCTrmagKmplMSbc8oxb2Mwd2QAXD/AuXNaZ2Mjvz+l3bOYPWQKppuneWcwC+bw5NApmEchrWS+Eumf8yUAV1j+LgdwIYCjpZRvhidaz8Kz1bEizU9gL7vtEkYL5kQyhfdLtuXkccKtX82g2NWSvX7r6qSfwWOVTXCd8Svtra11pU9esxMn3DMOAye7G3zY1W2kd4GHhm5PqH0wFwNBn+LIfyMXN3j19npcOXgBFmRcRHy8zGwZXm9Q3Nh1vfd8YFZyW9uXBSEpNgHgwL36dn4eFHALnxHrhKigFMw2x6z32GmhpsXkCy6cNjfnGbAbPNmcV+Lgb1dCZzWWm3jjOyV4f/E2PD6ha4eHqv2ubGjFqy58xPolzO5s/c5G13nDVHgY3S+8v9jcl/939MqcH7XZgw/+bbUtWGgTiM2I7koO2XcPZXpvjaJLt6CakjJSBZLOT/cOhYsPIJxnrD6AwkJKiVcNO0j8lRHodC1O99jvDrhiZsDYNZi2rgq3DF+Wk2bs3pz6BeO9VPlg7tOrsC2YrQ2L7hGUEqiobcGL0zdglyWOTD5mLdadoYD3d98uv/XdMM7Bwp6O2SnmdtaHE4jULVJKPKrZ1eKEXU/i9RZV1KktgN30NW7cDjnx9KT8K/SLjXKHndRvzd2E1o6k2neuyzq8+C7vDhjvS451sLT/nOXDZRW4a/RK/C6EeDhuZ3AqK2trut85lNsgf/madQZp78PsKpQjBynlUinl61LKwQDuBTAw893494aU8n0ppXoZnSjx+kCEaZIvpf2AwbgC+fY8b/4Jg0aEd4vK95hVqeTmroxdsQPnPzer0zWA3b1M6JyB2lCyeTeuGLwQiZTEo+PducXQDSB0QRSidrKvY8+A7iG6A7rfKGggRZ3+WkLiohfmYNKaSlz0whxIKfH3oUuc89s871bFkVvrWi/Ut3Zg+KKtOPmoTwUvzIakZUtpIa3N2LUxXvqD7OKgj2bJFjfdh3Eym21nVDKrilTVt2Z7l2WWykVGa3v4/U1Ulm1e2uUwW3DVuGD4otwtpde+vVjr1zjLBc/Ntt2qbKxTdw91t1jXlu63Zx91+QBemhHdIsRjE9T9+jQb9zFGwnjG3rP5Hd0iAUxcHUxRa7yEpybp/WI7saOuFVe/sTDHysrpGfa7A66YqTBscV9Qbl7kdTNpNh42LmBa26e+Be4iw4q2nQFwwfOz8dAna3DjuyWx+do3K2PUFef6Dc3Nb3WnprOQDoLdQk8UY6qd9a248Z0STF2bG1viuakbHMccAvDceZ7/3CxbQ6vRS7ZhyppK3D16BX748OROF19hGCnMLq3WZ3LAi8FXHJRXh7cD0Y4g7+qdo1ag/yerNRbM+graEkn86OEp/gUJkacmrndtvKYilUq7yrFzuwNY74v5HTCNmW1ewJLNtQ7leMetNXBO/5ejcA7e/quMC5wWcqPEb3vfS+TXgrkTKeW9UsoV4VVNjHj9TVUPkGd3G5C2FsfGAcO4lWZ/kbrGIV9+iewGz38fugQdyZTSmbsTf31rEUo21+JPr87PlJ+bx+namhVRec9/zru/I93KqM46Nu6tO5t2Ndtu3Ssmot5xbHQ94Qc3g1yjEnuZzbYo1WMkpcypI3drXvBe84YhJbj5vaX49wjzdsMtNf4UFFas7VucQWms2L2n1vZdJW5bZuu4m0moO3n055lX5dPCObWLVhcZOemW70allFGprOpTvAZrcYNR5jC7My9l5VXhYXPMuItAJYuTde7W3S0Ynxk76Leuq9H1d7oFzZSUeGGaf/dWUVOMvhytWNut/4xc4Wsb+LnPzrQN8lqMt6i1I4nHx6/FLB/KpPs+XIVbhy+1bT8PMOz2mbbWvHhh7C86HGJhuFE8A0C/gneRof6ek18C2+vS7dWsUutW7fw9YMZ3xe65No7/rel2v511XGZeZPAnoxN2/W1HBC/nv4YtxQdLK3LcagFw9L0MpJ9/VfwSIXLHVCu21WOG5R1dvrUON727BJcPXoDX52zClpoW16643Iwx+8QYQHPtzmjnZkEWO90QVEH5+pxNGstTfRmzSqtNO0DjYlVFPZ6YuA6Pjl+H0spgv+u4lTvwzvzNeGTcWtugwyb1ssKC2e7+GcdwQXe5u7ZgtnxX6YX8WzArFMwxjFn81tlLCNfK6Xs+WKkdszq2bpbgfnAI7pfz5/ZCiBk/gfmcsFvtVVFV39appLCStUS2NiS6B8vPe+onSJhTPQvKanJdZHgYPFZm3FPY/S5OE925G2swxXLvZ5dW41/DvAffGlWyTTv40CqYPddKwsZt0BS/6N516+Nrt7PAOBAea1lIEkLkPGffvG+8JY8bSdXYBYcDggciyWIdAEThuiSZkti0y7vVht176mWAkPVNap30+R1k5EzYpZ2/QpvznBQWHtfTT/1fl0WIsQ1XWWhHEUjDWGKY5etcKThLEYy4FhyveVPvaxrQj4F07cweOkvLAu8Q41aehvF8WK9h+roqfPPe8Xh8vL0yaPOuZvzx5Xn4xBLQ12m7fRTv+e6m9tADlNW1dOAfQ5dg0LQN+MpdY/H05FJc8vI8T2WUVzfh1VllGLZwK+bY+Kzcb88uBXOzJbaH0drfzioTsCwSKt4tXbDouLG2G/qFrPCMc/yQrd9cl7niqoY2kx9fN9fYljQ/AyZrQimxs74V93ywEstD8L1q14dZd4mFwfJt/mR18zuutTF+sQZPXLU9t34vsYiiJOgQdmVFrn/iYsLa5vlB1Z885tBnGVHFGHKa00RBbXNXQPRsIEI32I25jMYCunc6J1CmyQez2mgxaEwFt/POnLbTkh7GuEu5ezOOHTI+KxIeLJgHzy7HV+8aq8yjGjlMBTBFCNHP+F3xl00neUD1ENylCQxmxWmrzYMfr8aJ947Him11OZN73eqTH4syP0HCnAaLffv0CkXhYneOymr0cstK+8Uvz3OMaKvi70OXaLcE64IoxBG9tLtR6HdwsWHLkRu27s5V2BoXi+4Yad6kImC/Umw3OI8C64DfdzlWC+ZQSjVz4zsl+PEjUzFsgTdvUXaTNS8LjtnFwZydYL4tmC3fbd4C07YyNy4yfKYZ61H1Kd6Utu4Iw7LBDi99Y5hNuO4W6beWBxMm6LXodmtYgxJbGe6jH84nTQHdJQXFTXvxh+98zlcZT0+23257wzuLMbO0Gte9vRizN+gtfL0+Q8mUxD+HLsETDu5L6lo6cNL9E/DN+8aHGoB5wJg1GFmyDf0DBB417jyyC3BpNArZdw+z9b5xbOhswdz12WipZv0NCz3Wh03vqc6f00+6PTMcsvWZFzDNeQZZdlpY0+36EJUFs5TA9W8vxuDZ5fj1wJleRc7Bri+xcx04ZW0lvt9/Esau2J57gguMz6I1FogKN8onu/fCeFppZWPOjjprnqA02FiIuqXQ38uoWV+pjmUxZ4M+kJzKUG625vza5nblc3ZZZhd0PjC63/IyFrbrT42n2+oYDOk5VvqmMXPuqeZ+KT8K5lyfy86Gh37H+arnKJXn/sVapxeEEJ7uQXsy5Ti+ANQK5mwQv2wLeDlyA/xZg/1d4VoyYsKPW4uoWbOjAU3tSfxz2JKcwYPOgtnvds+Z671tI3S6b71ErsWbH7cedi9bvjp2XT01jeqgGs1tPSv4QBSEsUpeSKj8L3vBuGIe9G1Qd87htHPWlfgoPGR8nLHCu+393KBLXrEOElXbLZ0sAXxbMLuwlrJrSx1/K6md8jumGHdxuB3EhYUuIrZfjNfhZF3YJUP+sLtGVfAvLzS3J7Tvsq58rb95TQEPj/UXECpfbA7JHVCU6AK+eX1ESg1Kgotf0lv4qhZn7AL9fbSsAu+XbMNTk9bbxjsw7ppb53LLuJT6YJFrdwS3DjS2E9axYGNbAh8urej8ftLnzbELjIsxThN54zV8snxHpxW3SgFbiIQpbz6tDq0KYCO5z7m+TzYuOCRTEtcPWWw4W2qDsHrB1kWGjaLh8tcWoKKuFX99azFuG7HM8+K7scTBs8tzfI07MWyhejFRZXma5e4P7D2CuvW9rMvV3J5Aa467Ofdc9cMv+j63J3Dze/qdw7oxSTIl8bd3SvDw2DU5Y/LLBy8oCFd7C8trMGh6lyszTwYMdsc8GBrkWjCrSze+O4EtmF3OPHUWzGG4ElK7yOhKsy4cdskQbicbxAdzmMY0jqNFKeXgTBA/mfluDe5n+xeaZD0Mrw9EPgd97YncVQqdZaHfF+aPr3jbRuhUTTKV+6K8pxl0/MEQ2TQ7nrez1HarYA7aaOjquUcTgfjBT1YHqp8UP0EtO53ONhZrHGP5Cezxz2FLHNPC8q2bE/AzwvbTSQnjFDQjaJC/9qT9IojfQYZqAJbl9dm5vsOdZJbw3xb2Nfj/dDuIC4swLJjtlOLGou4arQ5rEe5lxacp+uPL87S16/or3YTCy9ZQkoubp0PXpnh9Xr0HpHbOf8XghaaFT8D8TOjeRbf1Xz54Ac54fJop5kZdS4clqFpwjPfGaklm9edsvY/G7E4KZuvtGL8q4yvdki/uYNE61KpYm/wKC7ZnHCzto0BlOWd9LnVWeIBZYWNVlIcVALirvNz6dUZF7y7YgltHeFx8txR50QtzUNMUvJ130+44WeaFpVNcsqU20PkjIvZxXOy4MXLTvRcfLq3Ah0sr8NzUDfjifz4xpZVsro1kJ6RX5pWZF128GPfZvQfG8+3aGfVuRLVRRhjKXK9Yq1HFqvE7T3FrJLW+stHWjWKY8Td21rfi2Sn+Yo30EiKeIH8kWrxbMOeP8l3NOZ2hLgBdnEH+svVbZXhqkjrC6nzD6nhWSTTZJqq6btVybsZfnuo3vf8jtXI4LUMhdF+kmKmosw++lUX3LKdSEhttlMZ2Qd4A4LRHp9pu9V5QXoMyB+Xz6CUVtseBXMvjnfWtvtqWpGUkGWXr5LQw5BSUxn6bmvmg6ldyMoL1O1Bwc96bc7sUzNn8qsUMvy4yjG4PlEH+Iu5v/BZ/5eu5wYmMsr4zv8uiq7Ujt0/1qtwpr25CfWsH7h69ArcOX4pkSmJHpg3Q/a4vzyzzVJcXFm+uDbzg2k/jY/k/I6P1d0/0hBlLxA7de2hVPhnlsXZ1HcmUyYWFG8VRc3sSU9dWYUNVE97NvLtT11bim/eO1y4WecW0VdkinFXUHAWkw2fzOVL5PcuKbf6sse0CROWDoDsloiZbvcqCWbeLSBcU0NqXhH3Jdv2tdSFjdwiKYDu5t9cFj8vhZLhQWtW1o8LJRaFbBfMkmx0VpnICqiezcYKIPW6MU3R5wljMcMvcjbvw+xfnoGTzbk/nWecbXto3nXGLTkmsStPFaQnscs3l+TlyGL5XN7ZhlGH+6Xecr5p/WO+X3a7oMIOU3/uhNxe5Rvr08uYiQ4drBbMQ4nohxERF+nghxF/CEavn4fXBDtuk3itOQQGzBJnvq65t6ZZaDFuwpVOZ4ZQ1JaWnF8XaQPTpLTB34y5T45NFF1T79xlLaFWj8YqLybzOxzIhOoJuK3eyfrrmjYWdkxjrgHt7XQtKKxvw7JRS1LV0oGTzblz0whyc/uhUt2J3UmOwSJu6thLffWiSrdJOh/UyorVg9vbe2rVT1kOqSY1TO+dbwZyz0c3tQM5JDs2EX5GWbWs7kqnOdtVL3UEIw4J56trcLddO/YJdMFgv1U5avROnPToV37hnPF6fswnDFm7F/z04Ed/rPwnjVu6I3Q4x6BrA3hY/syRkXPw+uuexyaNLKd04MlcAdbLqPbU2oW/P3WRy0eGV+z5ahdaOJG4YUgIAeGvuZoMcChlTEm/MKce5A2dijcKVhrHdbLYs2uqtsuzLMWIN9taetB9TvzKzzGSt7Zaznw7u69cN1uvT+prPOT9cedxilDtX2Q/Ld/1iQFcsBmkKEOiUPwh2fZh1t+d5z80Ktc4sYVyK02L4gDFrsCjjSsRpzOXWLcKsUr0PYBIdVS4U8PkyhNPRnkiPb+durMH5z832dK51uuHlmnTGLbZzE4e81jS7eYOxjch+bGpLYNlW7wYIuux1LR14d/5m7LK4EjWe9pB115zPx8HL7krbex7iDhOnAMlu6NO7l2dZVM2hFwvmPwNQmYCuA30w+6aQXWTYoWvEKmr9rzJnJyk1Te0YVbKt0yJyd1M7zn12Fm4dsawzcJ7TfbOzYLYybOEW/GDAZCwsr8lRpPUWAre/b28R5dZFRtBBnS7IHyE6dI9Qh09f6k3tSbxlsGK1csbj0/HIuLW4Y+RyTDEo2bwOIm4d3rWl8r6MSxg7pZ0OuwA0UdHbZgVKdd12KV76A9Uimx9yrancnadykaF6Dk0TbYdCZpaqffNHPVEIsqD7T4vfc6drzPrwNtfrvh47C/msBc6do1b4uoZwe6Bgv9HCcm+WPcQbbn4dXWCeB1zszALSk79LPbpDA/SWPqqFROuZa0IIVPv81A22bZvTu5ZKSVz39mL8d/RKLN1ah188OcPR0tfYTFz79mJTu2EtfprFJcKKbV3KY7vmprEtkeOuIOtiwa7v2eXD/Uy+fIrnKNs1fYHf/i0ssvUpLQE1PpftLjH7+41ZsQNrrf7EQ75Gu3tsVTBv2qX//Wub2/H81A2OrtWiMqRSBal/b6HaT3RYfSKnd/ETh6GeXXt/8Utm4wkvAWetO0xUz7YVewvlXCWwU7pqsc465apqaDMZ1mXLufjleThn4CzlfNIO3WX+7Z0S3Pb+8pzA9kYZKy3K2KiD/AH2Y6gwLZiD6J1qmtqxoqJOn9ElXhTMxwJQ7UFcmclDfODdRUa8GmbdC/EvFw72nVifGRxd/tp8/H3oEnzt7nE46raPcdL9EzrzZFfoncRISqltgG4dvgzbaltw0aA5uQrm3gJ7OGzJdRvkIWib0dOjBJPg6LbhdWgsyFQK6Ac+Xo3KhtacgbLxuf9o2XbTgZQEBs8qw63Dl3qOItzHoLh9WuPuxop1ABBl+2lnwVyumGzZB8xzX5+j5bD7IpTnuS3H6Z7q2kFjcofDQkB9i3q7dRQKZt1A2y3vl2wz+Yb1MgAMY6EBKAx3S0H7w0UhBqkiudgFwbOiC541ZsUOV3Wd/+wszHAI6Kza3dVi40bGLcbnb1VFPd71GHAMyG0LN+1qsh2nObVHiZTE2JXme3T16wtt81rLMF+7OW3IvC7r6eVb60yLVXbtjdWqC+ia+Nq9p16UFnknR/mqUTBbTohi94saibZEEo9NWNd5ZFTJNlOO3IUSq8I5V+asBfMGG6v8sMc7thbMHsdzAPDPYUvxv7FrcNqjU1Fn08dH9csEGS98tGy7aQGHFC9Lt+b3dxwybzO+cc94DJ5l7uOsATgvedl5t56VD5aad1nPKq3GPR+sNL1PDY6LmOq5h60PZjinG9uZrbvNcx7rnC176tKM+9W7Rntz7aBbHHAK2Kpq7/22CqoyrW2NnbFTmPOXoN3ZyorgAYqzeFEw9wWwpyJ9T006CZG4LZijXPnbf6++ANSN/2cP3EtZRiolbVfZ3563CQ+PXZPjjN66VaJPr1746uH7exE7V4aA96gQlAKkuNE9Qjolr9V3sZWb31uWo8S2ThSsA5J7PlyFYQu34o053lasjcHzHjdMzqasqcQPH56MsStyLUCz5CiYI2w/7RagVO5BdNvUdHixYHYzkPG8VS1bn0PZutKM1TkFj3UKuOM2PShBnxe7rYFueNugONKhUiL07iV8DZ7DjJJewCoqkgeyYywp7f36Z1HFp9BZp+YsdsI4zpOdZfzy6Rk6cW2xc8dQ25w7eXeapNm1v/PKajBjfe5k2FqXLrB2tuwxln7QbdvV0WnBbFe2eRwwbV0VVoU4EQ1CrsJYk9+Sbs0eNDCyG16cttH0/eWZZSZ/r7mKGzP2LjKcF1+8XNKHS51jYmSxe47dKkmy11la2YDJayo7j//0sWk5eaMapwVdMPEajN4Ozu4KH91TMt8SYE9HNk7EPR+qd/os3lzb+fnVmWW454OVrtulN+duwuDZ5aZ+9JKX7Z9XuxKNbYtdutn9kvGzxEqDNfU1by4ynWdtn4K+2/5dAHZhHS/4t2C2qSdTlrUtb0/YKPVDVTAXzkjbi4J5HYCfKdJ/DsBf6EISeXCUsPGxWO0aN9aJF3z7swCctxklU9J2lf2OkSvw3NQNmL3B7B/LGGwJAHr3Ao4+ZB+tHKqGIeiqVJhbFUjPRKcg0inmdJNau4AUKst7Y31e3ej0cXB+fvngBdhS04K/vrUYz0+174Ly6WvNuw/m3GPWpktlie5oOWzTRg+Zr1dY5pTm8tY5usjQWpR1YX3eZOdx3UJI+L+vylLDc1k+Tx/iQcG8bqezP9lttS2xjxnybylICokXp6eValmfxX7w+p7bBSxyCoLjJ+iWV3mcdv5d+sr8nGPWorMTdCkl5m7MVWxkXSRY69BZqWVZn7V8tclv7LdLNu/Gn16dj18+PaNgfJga0VswW75b8ieljLytXGQzbtpgCDCX6xJDr0RXjdW8XM/f3jG/n9WNbRi7YgcWbarpfAbt7A7c7kj71v0T0NyewM+fmJ5TjxW7sU2UPpjdYreo5JUwF29JPAycUhpp+S3tSdz30SoMnl2O7/WfhCsGL1Aa0hgx7vha5mCsp+sb7OPDdB0z9gsTV1difrmzwj13YS/YO6hq599RzHNUY/lr31rkmKbit4PmOKZZm5p2m3YyzB1ChdQle1EwvwPg50KI+4UQ/bIHhRB9hRD3Iq1gHhK2gD0F7y4y4iXKgeXoJRVYvV1tHWG0ZrQjJdU+mHX+4fr06uX40huPWrenZJldWo3dTcEGIeNWqqMQE6JDN9mybte1ops0CNj4C7TkmbK2y0rFuIrt1QWMVXFrt03xf2PX2J5rfZejXOXt09tLt2o/0PIyAXL2fZyb8Mky/eBUte1NLYe+vdTVZ3WRkU3SPYdR+NhW+W/1Xla6hG0BYhMEoV/vXsGvIej5cQ9aSEFg52vcLW58FU5avRO/GzQHay0+lrNnvu5x58z2upbOXTnW2u0miyqSHnZaWK+1tSNd19S1VRg8uzwnf7ZvtdZhtIbLYtdWZ8eydhIaI98bjTNaA7gssSKlxNAFmzHTwXWK83m55Xg5YZ7FCjF6f/72yuD99+zb+VkXGMo++Jaz3EEW9656fSH++tYiXPD8HNzyXtpvt5sgfypKKxtdKUJsfcRCdsbl8YsbWXW37JMA7RgpDI78lHondNwY+5fKhjZMXlOJv761GMu21mrPdfPO2xmhGOcedq+J8dgfXprb2Qe8PGNjbmZjXdbvAZvZ295f7tjWO8XP0tW7oHx3aHPDbCnW36Hdxi1lmMYXcbvPNeJlJvwEgOkA7gBQIYSYKYSYCWA7gLsAzATwWPgi9gy8jmniNoOP2hrJuF1MVb+T1UkypW5IdIPI3r2Es5LHcHi1QxTwi1+eh7fnqycylQ2tynRCgqILjKV7D3QD8V69RM579htLFGRjEIrsJBnwo2A2d1dnPzMT66zBbBywvssS9h19GHi9LjvdqPW2+5k82lo5uVDE5k7Y3eUPY17u10WGztI+KEG7u+y9ucrG32o+tmSfcszBtn5XveDHx6YRKphJUNy8K1e+vhDzymrwp1fnm4MO+XgAt9W24JT+k/Gt+ycgmcq1bPXah3hZCLPKm/XB7OTC4MGPV0NKmdNn3zVqBeZuNO/Ys7uPvzrhcAD27+kFz8/GR8vS9RrHDE4Lf37mJzNLq/HvEcvxx1fmeWprcpWvmvyW7+8vtvo/lpEGYJPS/r6ptqbnPLt2ip+UYxK27PYfcHFJxkcq0LUIYTdu9NIHu45j43A86O+jGve+u2CLdv4JALsDWjFPWOXOXz2JjnwakVv9rLuhykFH4GSRbMSVgtnOuMXkPlSdDgATVu10VZ+bRTKvzCrdpc+kkcNK2AuM1uu0DfIXpgVz/uLZa3GtYJZSdiBtpXwbgK0ATsr8bQFwK4AzpJTeQw0TAMATE9cpfWhZiXuuFrWC2WtjZSUp7V1kdKZrXug+vYSrVe69+/ZxTKvTDEAYKIJEzSrNTgAdWr+PSek6sBMA/PiRKZ2fvbqSKNmSqyyft9HdAMP6Lr8xZxO+/cCEnEAUdrQnUvjn0CXaFfosvXsJVDe24ZyBM/HEhHXatsZ2G6gmirybNNsAHT6thtzgqFTwYFBmHXxJh+NWhmkiv/vB5L81YI8rIVFa2Wi7M2fE4q2elbcbqxpx7VuLchRHTggA5Qq/t07MK6vBH16ciyVbanGvxm+gDrrIIEHRDcmMPcqO+laLD2Z9+VJKXD9kMa55YyFSKYmxmb4tmZK2QRDtFMxbFLvjVH1Bjn9nS96spZjTAuZ7i7ZiZUW97XuWVQ53ymGTZ78902NZp7Yu69rE2BY7jZGvdAhcqMK4EO3FGtZr0D7dcxB1QMOhC7fYuoMwyq2zYLZ7jlRSD5rmbuziFrt7vK22pTNAuw63CmY7pPTnzsaIbkx2x0hnC8iweGlGWeR1kMLh70OXeD7nTYfdNm7GUp0LToq82ddgwqqdeDfjVsLOrZSq7ux3/cJerpFPUJrau/pkKSXemFOOKQa/7m7ksOJml5Qbsi2Um0XpUIP8hVZScDzt5ZVSdkgpH5ZSniil3Cfzd5KU8tGMApoE4LYR7ju1+C2Yoy1fNwDRNRKplNpFhvaFFs732Fj3Pnv0diziU/v0c0wDzNachBQiOourFo9bZNsMnauXSUZze8LWirXNhQWZlBK3DF+ac7yhNYEBY8wuNa4fshhnPTUDLYYtwcMXbcX7JdvwwMerHS3ojO1JaWUj7v5gJZZtrcNTk9abLIDs5TN/X7ujAU9ONPuhH6tQ4ju1U7a+nZWS2Odx29Q7takSUulv0NieOm051036x68K352Q6baGYMF8xuO5QYwA4JbhyzwrNe79cBXGrNiB378411bxZUdTu/ft7Ku312POxl0479lZns+18tqs8sBlkO6NblyrX6yzlue+bCDtx/zjZdsxftVOzNpQbVIWzy+ryanArr268vUFjuWr3vN/DjP3UdZrnbR6J6RUW9dWN7bZ1mHd/WO3cOxGadHYljBds9PvMVkzybfDqDf3MuH2bsGsnztEzYaq3MU+VX/jJpBhPhfwnH6fnz0x3ZXbFI2Hwy4iuiRdf7tAs/OPdA+CLlS4YdC0DY6u+3Q4BcPNtlFuYkBNV7gckjLtbubqNxbitveXY35ZjXKhy+lYtiwl1jYthHfbeP1zNu7Cf0evxOWDnftfN/WGZQGcrcZ6v/4+dEnOAmPQtntDVSPenb8Z7YlU7LpBI96cRZJIGWnZQpFIppwn7TE/Q1H7KdNZc+uq12/917Qi0t3Ypl8f51dIFySw2ceEn5B88rUjDlCmB7H2aU+mMGLRVld5K2rtt4pt3Z3r0/aOkcvxzvzNeGriekgpsXRrHXbW27sHMCqSm9oS+HjZdqzeXo/hi7osYrfXddXRmmmXrLsTrBa2Hxt8HV/wvNlliBVjW97akcSZT07PyaPyW+rFB7OrbXOWPIs27dYo8t1ZMLjByWI+KncmKkLULwd2L2Fl2rqqzs+nPTJVm18IEbu/wRGL3b3rpOeinfx5tE59cuK6rjRN3UKY28xLX5lv8nV89RsLc9pUu3ZJFWxTNS61jv+t1/r05FK8MrNMqRTpSEpbP89WRYWdHNlDqlv8zOT16Eh0ZbDr//3ODYwLzl6syHIXFYJZMOcjyJ8dxt/bev1XDF5o6kNsleQufj8rm3Y1YdJq74uzKsXWXaNWaJ8BJ+OCGeurTN/td3cF31FkZ0FuhPH3SBhUNbSh/5g1jsHHdXx6vz1tj2dfL1V/mE0rq3Luj1LS7Ef/t4PmmPo0u+KdhrI6Dzle22k3ZNvJjmQKF780z9U5ujFEWBbMXfXlHnvWEhwy6K6Znz42Dbe9vxwvTNsQu27QiOP+fiHEjwBASjnd+F1HNr8bhBCHA7gJwHcBnAxgXwCnSymn2uQ9B8A9AI4HUAngFQAPSikTlnwHAngYwPkA9gYwD8A/pZRL8lFmEE754sGdnzuSKRx35xjss0cfnH7cp/HB0gocsm8/XPq9o3D1j46O3Qw+chcZmvm4tpHQvLC67UkSCgtmw+Gpa6ts83QWoqBvb45iSGHz1cP382WN5AYvg66359lvFbMLdvT2vK4Iwkcdsjf26uu8yyBrjVVa2YjNNV2TcKOFkdnnpMT4lTtwzZuLcP3px+CWM78CwJ0ltRPGydLvXpzr/XwX7VQWV4F1bI5VNej993qRwy49lZJ4bVaZJS2dGOT+hkHQ7m7TLrUrFrf9aUVtC4bMM0fI1k2WCSkWgo7rrIon464XN69Yb4+apeUe3Zx5CYpnN+l84OPV6nOSKdvzpq+rQkt7Env16+1Ydvbeq27T9tpWHLrfHp3f7ZTZOndGThhvvV3wKbfoLJB1j0HUxjNOGKu1E2HQ9I24/vQvAXC3dV1H/zGrfbnO2FjVqFTCvLdoK+479+vKMpy8o136ynysf/As9M0ESnaKvVBIShTSfQmqBF1REcwN5gmf3R8jFuced+OWIpum3D0oJVot75hxfGlrwZwTML2rLBW5wcODkxVl6AL3LvJaOpLY1diGg/fdwzY9ah/MQHr3rBHVvUvvWnI3Lvlk+fa8u6JTGUo6O5AFpgKQQoi9Mr6Vp0L9TIhMuvNsPpfjAPwbQCmAZQC+b1uwEGcBGAVgMoC/ATgBwH8BHJL5ns3XC8DHmfRHAewCcB2AqUKIb0spN0RZZlC+dsT+nZ8Xb9qNlEw/iNnACtWN7Xhi4jpsq23Gj7/86bCq9UXU28jC8KMmhHM+dwoTh+OZ/+tbO5TKt0KK5kmIH56dElrzFgi/2+tXbKtT+qHuSKZQ29ye475g8OxyfOHgvXH5D442TXw7kilc8+YiAOl784fvfB5HfmpvXPKyd8VwFmNTulTjTsPp/Hfmb845btt+ubJg9ixCRg7nyaBqeJQ97e15m/Cuw0DRS3yCsDBtrw/Yluv6s/llNa7K+cljUyNzrdS3t1AGU/zU3n0DBzYiRIVW+ad5j1SGCW7GlL00cQGCzt1ueneJ67x+JrrtyZTjdfYfs7pT8Wfrw9eFBWwilTL5gLbbCehXwWySxUN769lFhs6COTYFs3ExJFcGY0Bju9+4uT2JyoZWV/duS02zK+WynRzXvLkId519vPI83XuqUpgkkhIKm4C84Ead8+n99kCli3kkKVyitlS//DW1uwYdTm9Rp3WyIq5GNo+qS6tr6cDPnjDbhBpdINkHCreXSrd4mmvBrMzuilRKork9gTtHrXB9zq+engkAmHP7T2zTw3IxoVK8W3c0qrqc5vYk9tmjS1Xblkhijz72DeSaHQ2dsRQKAZWLjCsyfx2W705/l2f+98IiAIdIKY8F8Igi36MASgCcKaV8SUp5I4D+AK4TQhxryHch0krqy6SU90kpnwVwGtLP9t15KDM0VFFshy3cGrvyMuxtBFb0g8Ts8px9ejIERzq6K2zRuLiIaZxKSLfCLjCaWzqSUhlpuCMpHS2ps0HNehscBt7+vtlPflZhYAxQ5BUp04Okks27fZ9vlQsALho0OzdwlKs2yVvD1WmB7LO9y/Zlszfk/k4z1lcjlYpny3J1Y1vnQmrQ+nXnu3UB4qRcDmNQfPA+9hYdWY49bL/AdRCiQqcE1lunKiyBNHULobdgDvqWeQm6qwuwa0d7wt6CGUgHtu0s22Z83GXB7FxvMiXNriwydZVWNuDMJ6Zj9fZ65SKVW7z1JdY+Tn3yC9PUi+ZxKZilScGcm769rstNmN1vfN9Hq/CdBycplU5Zal0sFO5uascPBkzOOV5a2ah/DyPusN+aa7+jLSyEMAcQsyNIoEJC1uxI9wVDF+Qah2Rxeo2yr5/Kt3O2HVMt5ugCtNu9x066H5VrqHRZ5u927fRvX5hjO5dxIpmSeGTcWtf5jby/eJvt8bDa/x31rZBS2vZl1j5S1Vye0n9Sp0xvz9uEr/13nNK1pNU6Ok4cFcxSysFSytdl5gkzfFf+ealcStkgpVSGQRdCHI+0C4tBUkqjRu+5jPwXGI5dCKACwGhDHVUAhgE4TwjRN6oyw+C9RVvxwdIKNLR2oEPbgYdVqz+irl83QHHjgzlI9y8VftiysunKd7s1nBDizIeZHRx+0FlTdSRTWiuUvgYTgAmWYHJrdzQEnkylJHDuwFk4/zm1r2YnnGrfUtOCupYOS169rH7HV44WzJo6s6d9/bMH2KaPXmo/EMwHWRcsQZtqr8HJvOLGjY3uMd1Rb+/nPEvQ6fRvTvpswBJIdyeodanq/P6frNa21YWkNPIz0e1ISrRoFGNOZXceUlSbTEn0Nsway6qbUFrZgDMen461Oxtw1lMzQrFg9rLN15o16Lg6LgXzlDVVmJJpx+36zPllNVixrS69rV1hLTh6iX681OpiR9BLMzaios6+T9DdI9cGQj7pP8Zf0DS3CAgs2xrMvQEpfhZGGOzxF0/OQCol8e8RzgpVp7fETRuVXQRS9Wl9NG467WrxsnvdtGhmSbNbQJ1fXoN3MsHq3JCU0vfuVqc2KEzjyQ+WVtj2R6t31ONHD0/Bi9PTi52qOVJ9awK7mtJz1DtGrkAiJfGv95ZiVEl88yK3uAryJ4TYVwgxWQhxZdQC2XBS5v+FxoNSygoAWw3p2byLZO6TMx/AfgC+FGGZgalr6cCN75TgqtcXaoMC5dvPipWoB2FuByhOzWNQp+mA80ufParzi6NVrNCFBiFaVAP9b37uQOW5KyvUFmNuou726e3cTTa2JUJwWSCxvlK9+q9C1Rd4WSn3kscL2oW2zP9OA+FRJRWxKX4GZoJxBF9EUJ8fVCkzaLp3X5peCfoTfDbmIIMkfsIIwOb3/I+WbceM9dWO6R3JlPYZz2eE9g4bK+OLv/t59TnJFCau1i822U3u3fhgTqSkycr7mjcX4YzHLVusQ/CX7/Y2p1IS8yzuhYLOjaLenenEwCmluHzwAmypaXZ09XL2MzPxnM+AYUbaNGOWFdvqlPVo73EA45q457Zu0S3IkuJn7Eq1hW9QdHoKp/7mkXFrUVrZaHJXZCUdrFRisWJnpG7Hjt276EX3Y8xrvZZfD5yJ2mb7nfpu24Ag/bGjdXiIHuienLjeVs+zsaoJm2ua8dAna1zVaddf/33oEgDxuA90iysFs5SyEcD/RSyLE4dn/t9uk7YdwBGWvE75YMgbRZmdCCFqVX8A7E21MswrqwnFCiBKolcwh2DBHHBGrGu7dMUH9QVHCAFmljorBXQDjCUan8btyRSO+8z+yjx9NH45G9uCbUkK2pSqzvfjIsPPwldDa4ejJYG2NBdz1bgMC7NukII21br7bvSx5ofD9rePNh4mcze68xPtBPs7ohs36gJWBg3+vFOhFLphSInrxTC/7NPPvXNZu3vVT7HYCagXqs782mGdn+0UGx8v247GtoSyT02mpNZPtW5R1w1uFQevzirL6X+D9qdxWTBnWV/ZoOyD/W4JN6JTSqi23gP6exxk/lYICuYC2shAIiTun1n1rO9WuEkFgDMen6acmyRTEmNW7MBwhTsFrQ7Dpjuxk/mRcfbthbGfsbvSNw1um4yc9+wsrHARQDeImszROjzE9ifdn7qRRZ1JCGC2wzx4d1PhxkVxpWDOsATAVyOSQ0XW7MVu5NlqSM/mdcpnLCuKMkOlXePHLO4+OOpBgDYgi+Z83cqgMRK2VzTun3MzOkAfzYSo+fxBeyvTgzZDHcmUti3QbSPbXNMcSAadL3cdqi1r1iQpJRLJFP782nz8e/gy23O83lOJXN/UVlQD2ezgyilPa0cytolAS0cSze2JwJolncJEpzjSYVQeFSrcsUN047InJqxTpmuD/AUILrattsXWN3GYnHNijj2KCaNyU2dlake7YsZ9/OFddi0rK+wn789NKVW2/0mLBbMdA8asVgvpArctxTOTS23ODWjBHPPAvK0jpZ0biIA9YpvGynyffroFz2DzM9V7Wgi9RNyKR9IzUPWHJ90/QTsWV1kwp6R0DJqdRbcz0NqWfrxsOx742Ny+p6R0DAafXfCcvq4KHy/LtdN0urw1Oxpw9jMzlbIBwZTBTvM663xq7Y4GZUw0Fc2aBdssOmV6Iilx8cvzco63JTLzkwLFy6zmbgBXCyFOj0oYB1oy/9tpAfY0pGfzOuUzlhVFmZ1IKQ9U/QHQLs1otxLGHeQv4kGY3n+xWimh88H8hYP2DrxKrXeRoSaf2y0JiYJLNFt2g7KvxrIzaDvYnkg5KmizSj+dBbPO2kfHbodtYm5RtcV2A7AJq3Zi6toqDF24BTtsfCz6uaMf2QweO8tzuZPD6S63dSRjtSg6/r/jgistNDchaH+qmygUwoSZ3R3RKZjf1/gV1Af5C4ZT4J/O8gNWcOh+6p0GRgtkOytT3ZixI+Gc/sTEdUgkU9hS04wnJ663zbOzXm1BnkxJ9NYsuKpcSrnFrQGL3fNQrD6Ys7QnU0ofy2GgK3/vPdSW9rp7rDUQUlkwa+7/Y+ODW3ATEgbfPfqgQOcndYaEih7t4H36KecmKak3XNAqmC3VXz9kcU6ejVXOQUWzrh0ue3W+bbpKQe4GL/6grTjdG2P7X7J5N858cjq+df8EX3U0tSddjUlUfrgB58B9vx00Fy0R9xVB8LIv848ANgOYKIRYCmAdAKvplpRShu2nOTtztXNVcTiA2Za8hyOX7LEKQ76wywyVoAHkoibqMZh+i5U6XevbCOl77JRLwnkwnz2qDUQY8WSIkLjpG8JkUoXWEsaFkdePv3wopq2rsk3rSEqFr/X0cd2E+eB9+umFUNDUFmyAoFJezttojqErZXrQk8XOX2bYC1/6xdI0jouFMri7o6A8H9DvpdalU1C/oZoKGtoS2FabsxaeV9jfkZrG6BbTAH1bo2tFgu5G0aKRry2Rwp59eztm1b1DHckUvvTpfVHq4NNfp0BvT6aUdaQNN9R38YTPHuBYP5D+jbTGGS4bC7txfhClAxC/grmtI6Xd1RS0O9RZMGefQSf0xjPqdKUFs+ZclR/1sIh7vEHyQ0VtMD/aB+8bbOwfJKZAa0cSvXs5z02SKYk9+ugUzMpkVwt92TgldnSkUpi9wfl9DapgDtJW93O4N8bfZMRiZ/cibnFrLKmipcNewbx0S622LY8TL9qBPwP4GtJjtBMB/DZzzPoXNksy/59sPCiEOALAkYb0bN5vi9ze4bsAGgGUGvKFXWa4hDQAi4roXWSo0/XRxvUvnW71zrHxdxEMxU06Z9yk2InaCl9KiU8rXFi4qf0ghQK4I+m8HdWtK5xffP0zLqRwJqhyUTWh/uewpabvEuadHWG041JK5T0G1Pcw+ww5iZJMxb/bY0HAaOJBFyN16H7H+WXB/CeHQdxjFhI/j00IZn0YZEIeBkF3Muhec+OCn13WlJRKP84dyZSyrd1c06y8h20dSbWLDOm8IJvllGMOVqa7aerc9kt21xJ4sS7mhqot4c7qLQhaBbbmfL2vcv/vaTZp3c4GjRSEBEPlUsgNQZsKnUsmVfEtHUn01e4mUafr/OkHvb6mtiQufinXtUOWvT3EJLAjyPzFaRHJOBYPI7i4dteRxoodgDKQfNxzIxWuFcxSyl4u/oI9Lfb1rgSwBsA1Qghj+dcCSAEYYTg2HOmge+dmDwghDgFwEYDRUsqOqMoMm7tHr1Cmx/1IFUqQPydrCjfRWXVth67vcbv12wmdjIQUOvl4hFWdvJvOVfWeN7Q6B2FIpCRKNu+OvK0NOkDw8hukJGA0erBrZ/2Iowou1ZZIYcpaewtywLAjxCE9mUoVvXJS11+q+gI3z0chBEbSoQqwRnoG2wNajGkXajSvgcLgy6UAmuSAO+9KNnctZNlaMGvqf2VmmbK/GzilFC/P2OiY3pZIKZWDyZTUt8UhWGy5bc7s2tViD/LXllAvEgDRK7b23TOYazKdfHUtztPm7DtyzkC9D9aoiPsZIMWBKgC5G3R2cEpXMhI4+pB9lOfrLIR1lvrG/qrJRzDzRgfXDlkO3dd/LCwgmA7FyajDeNg49/Q7T9Od5Sbug6o9KuSmKtr9zS4QQtwphLgTaYUtAFyaOXaDIdstAL4FYJwQ4mohxFMA/gNgkJTSGBVkOIC5AN4QQvxXCHEdgKlIX+c9lqqjKDM0gkbpjZqo6w86UE8m9Qpk1VY/KV24yNA0HYOmq7dV/2ek2u8OIYVO9O2AWkHspn7dll7Ve3z+c7MDLyTpCDqZ8WpxZRo02aT7+U1VCmbdIDxbnVO9iVTcEQeCo+3PVX60XTwfAQ1x8sJIjX9d0v0564Rguz3GrdypTNcG+YvYG7l2553m/H+PSAdebU+k7Bf/NOcnXLiw2KDwmTln4y5tkD8dutbaTXcXRMEcdME2buViWyKlHPN874sHBb5G3elHfipYcGXdPdxU4/wMZp97ldVe1DT6UKaRnoeTb1y36C2Y1e/RAXv1VabXtwSTz/gan/XUDM/n6+SP2jWcCqexglOZfqvSnaeKm5BFdZ8K2bbEtQ9mIUQSwKVSyiEO6b8DMMSHFfP9lu9XZP7fBGAgAEgpPxJC/AbpQIPPAKgC8ID1XCllUgjxSwCPALgRwF4A5gO4TEpZaskbepl5JeaHKm4XGVmcBmJufDDr5hraxkuTrAuYQkix8/a8zZGWLyE1Fsz6MnRuvgJv94x427T2fA8FWP1f2k1UvTbtEl3BPPzQuWDnUIQrq7kCR7sgqkhPpCT6aEZVdgHBCCk0gm451S1SBI2orhNP1wzpxoy6dmB3cwceHbcWL83YiG9/4VO2eXRWZ0FusZ1PfiPptjiY9aqb/jLI/CLo3CSou6KguPFzHVRC7fku4yY4oXsP9ttToRgrgL6eCmaSD/QxBdTn614VXYgcbZwogwB+4hPo3D8EXcwLMu9wOtep/0hJid4+Fqi1LjJcWDCrfqe4jU1VeAnyp7uzvoY1UkpX50kpRwEY5SLfbgBXZf7yXma+iNumy01wrUDlB/RZ2TVIc7BClvoHVuvvT3M+ISQYbgZYpx93qNIFQ1ClQdT9d9T+d41Yc9qd+uJ05y3UTkTp7ifIILJQcNNfOeHm3t774SrPMhGSb6L2F7h5l3oSHNSlYpDgZW7OB7qCJs3esCsnzc24VaeA/vJh+2LdTucgfB8sdY5bnnCx2BdGfxrkKZlZmnvfvBC367pESv0jp2Tw9yj4b6hRmmi21Kj6w8qGNlTU0Z0S6f4EbWt0/Y0uQLlWwe1ZIjO6dqCqIZgRXhDl6oOfrMZ3jz4o57izBXM0/YLuHgE6F3phShMuYbrI+DwAeuXPE3E/VFEHwtC7CFGnu1HA66xpnAZBui3dhJDwUPnNTEnpGA04i95nZLBBVmAXGXncJmatynrmgvIarM13cJ2MUE6T1pSLwFKFju4nUv2GDa36MA86y0NCCoG43+Lyau9WWEZ0k0G9RZo6/bTjDtVIoL+DqlHtcYfth8MP2Et5fk1Tu2NayoW7It24+KXpG3HbiGUav5L+n5SlW2p9nwvEH+QvmVL7YJYyeG8YdCEkqIsMVf1nPzMT5z07S10BId0A3bgt6G4RXUMR1JBPh8445IGPVwcqP6gOZp5N8Gun9t9vVbrz3LhZ6ZYWzEKIc2EIbod0ULwzbLIeBOAMAPF55e9hxP1IRb2N7OExa5Tp2SGWk45YSmhNPXTWLE6XuHxbHbbXtcSu5Ceku5N+jdUuMtoCKte0TVkIVmkqBmjaOh3eFMzmLc7WwYnOAtC+TM+nmM/XlOPGaq7Q0Q0CVRYKHyypwF9+fEzYIhGSd6I2Dv1w2XZl+hMT1ynTddbBt7+vjpsxROMySnf9Pzr2UExVBUQNOK5Nu5xSn69iY3VTYOXjYxPSv8HJRx2EC799pK8yoiQZ844ZnVVjSkb/HmkVW5oZqO4a4vZzTUghoFcwq8/XvUVBXTYFfU3dWOcGIYp2xKjbUs2VXJenOe/ZKXpPuzoXeoWKzkXGiQD+nPksAfwo82elEcBsADfYpJEIiHvCHfUz3aDxgRXUwhnQWzCrijjrqRn4+MYf6ishhPgm7TPYOb2xLaGckAPBt3sGNBKIHC9tsTWr1dWRH+utoNefrdKpnO4wGQ1iKRK3RR0hYRG1YcKiTbsDna+TThew9MFP1BZZ+gl9sMXML316X01QXL0LDR36mATu2Fnv7AYhalcqKuJubxOaAOXWRWI/6IOo685Xp+ssF28ZvkxdACE9gOnrgs1ddC+ifqFHUzwkttQ0Y+raSp0ktrRHrGCOYjgRdpA/3Wludtwod/sU8PxIqWCWUt4L4F4AEEKkAPzRKcgfyS9xm8XHPQjTD7CkepsZ1IYgEupBXG1zR6yDYEJ6AhuqmrDfHs7dVFAfXkBwFxhxtwNPT1rvOq9VVGs/4leZK0SALWSZX8DRgjmZiv0eB0Xrg1lxfZ89UL2lnZBiIe5xo46gQQh1NGq2w7oJkKeScL89+0Tusz6oyyk3xDlnjntBUxfkTyK8RV1VHUHOv/HdEk/yENITye7mcCLoe6rL4WZB8+dPTEdLh78g0lFbMEehB3Nq/v3WpTutt4stRaq6C9mC2YsP5qMBjIxKEOKNuB+puCf82eqdBmK6IISplNRaSedhHE0I0aB7T4MSVIEcdzOwQ2EJZsVqfWa9ND+TayllYMVMKiUdt68nXfj9LHS0O24UGXQ+UwkpFipqW+IWQUnE+mW8t2irMl0bWFpjgZxOV52vVlC7IawdPTpXHjpGL9nmsiZvxG28k0iltFboQTtEvYVysDFPWXWTN4EI6YHs1be3Ml27W0TzIh59yD7KdJ3hQ0pK38ploDhdZBjbPmPp0ueljF+1Q5l+5Kf21pahuo1JnbIrRrwomHsh7WfZFiHEr4UQRwWWiLgj5kFQZX1wy8EgaFfeoN5mtnxbnfL8LTUtqG/RB1cihBQ2ga11tBV4ECZmpDTfD2s76ndyHURpISUweY3zFryOHuCDubSy0TEt7sVcQsLijTmb4hZByfiVO2OtXz+uBVoVE379zrwQlOghxSRQLUpa58wJmxn2Te8ucVeRR+K2YNa5yICUgZXgQZds2ScREpy/amJr6F4zXTuwVz+1F1zdgubYFWrlqI6ORLTtRDFYMJdsrlWmn/X1z2jLUC0EFLIFs84Hs5EHAXwOwIcO6f8CsBnAZUGFInrifqQGunBMHiUSQFsi6egTL4x3bsZ6tb89jrEIKX6CRmouJvtaJxcZK7bV4a9vLUK/Pl7WnLvKCKK0kBKoaWp3TG9PpIrqHtuhe4ZeVyjeCnj8SEi3ojHi3TI6dO1EeXWTMqitdjeJxgLaDfqdfe4aLKMUyZTEc1M3GOroKmNDVSPOf3YWzjnxCDxw3gkAgD++PM+tuJ5pbvdvsRcGOhcZKRl87hE0UCO7JEKCs3RrrTI98NwkoK/1tzVBa3VE7oM5iiB/Dvcszp0tKiVy3AuiKrzMJk8FME6RPh72AQBJBPR05WZKSrypmJTn4/4Uu9KDkJ7AiMXqbclR+yMsNIztVnZsctXrC7F1dws2Vnnf2iqls6sid/Loreo27Wr2XX4hEMT3LK3FCOkZ6CaLCzVBDLUuMhBst0m2DhVu57u1hh2CIxZtNS0yGuv47+gVqG9N4K25aWVHZX2rNtiikf/88iu44gdHu85/+/vLXeeNAl1/KDP/gqBzYaFTprQF2DZPCEmj2rkH6MeNQYPGRh0gLnIXGRGMjetbu/ol827P0KtK1+Eij+o6o465EAQvCuZPA1DZy1cCOCyYOMQtPX3SKSVQvst5kJSP+9PDfwJCugW6yZrOx1UBLyDnYG0Xs9+rG/27PNIpNdzIpLuFut0khc7sDbt8n1tMzxchxD9huD5Qe1cIttskW4c63R3PT93QqVC3uqwz3oa2DnP/2+GxQfzhsYfiv78+Hn17R+xgOyS0CvxU8LnHB0sr1DJozr9r9MpgAhBCtOj0s7oFSd35UVvlRq1gjkL8G4aUYEtNrkHL1t3RGLm4uQbVQkAhB072omCuBaByGPMlAA2BpCGuKdxHKj9IKTstGmzTEcyqzg1jVwbzT0QIiR9d/6wf5BVukAUrEvar8kEGKUFdZPQEpq+r8n0ud8oQ0jOobAgW2ySV0gQBRPBxcdBt2UaycU569zLLZFR8WJUgXqXP3o5iWahzo8CP+loKWGdBSI9BpwDWB4UNdn5QovYPHFXxg6ZvyDl2/nOzI6nLjZJftZDQXVxkzABwtRAixyN15thVAGaGJRhRc++Hq+IWIVZ071Q+/OUMGLMm8joIIdGiayl0bUkhB1mw4hTUL0hzGVRpwcmsmiJ6vAghARgS0OelzgVG0N0mAPDJ8u3BCjDww4enYN3OXLskYz9lbf68ju2zfVPR7PrUWjBLTFwdbTBKLmoSEj9aC2WNewTd+YOmbfQskxeidsERVZuejWOQj3bQTQ2qPq+Q559eFMwPAtgXQIkQ4mYhxBmZv5sBlGTSHopCSEKs6AaZm2ua0UI/YYQQDbqFIt0gqZBXkO0wihvKQlxQFxmQ3JKjIPsbGX3DEUKIFZ0LDIngu03KNf7wvXQpjW0JXPn6glzXTQDW7mjAPR+sxNbdLb7LB4rRglnNWhuFfOgyFMm9IqQ7o1Uwa17Ul2eWhSmOZyL2kBGZIaGqiwxdae7iGlRK5KiV+EHo4zajlHKJEOJCAK8BeBhd/aAAUA3gIinlwvBFJCSXks21OPVLhzgG+yjZXJtfgQgh3RLdIK6YFMxSWqzDQhA9JdV+P93IRJzJKl/u+YB+Lwkhzkipbk+DBmR1JYPH1cItNS143RKwW0qJM5+cnpP32Sml+PU3jvBUfrF5b5JSsk8khGDw7HJl+pMT1+dHEJ88MXFdpOUPW6gO4O6XrJspazt89+gV+HBZeDt4AHcLn6o55gpL/IJCwrWCGQCklB8JIT4P4BdI+1wGgHUAxkspW5zPJCRclmypxXGH7Re3GISQbo5uAFDIW5SspH0wO/u39FtmrwBmcTVN7bh1xLLAcnRXsj/RhJXRbosmhBQ3UqPezYfiMozu0KmMR8atxU+/+mlPZRVbfICUBGpb2mOVobSyMdb6CSEkLpzmM9aF0DBw4+ZDZaX83qJolOxh4EnBDAAZRfLICGQhxBP52CpGCOnZ6LYgNbQm8iRJcKSUpsn7KzPL8INjDglcZhAzsV1N8U6mC52ZpdUYu2IHGtqK5zkjhOSfdTsb8c0jD1DmidqvZBg7eu4cucIxrT3hdd91cWmYl2+rQ1l1U6wyjCzZFmv9hBASF/lclHRlwVykW1o8K5iFEEcBOAPAYQDellKWCyH6AfgMgB1SSs4WCSGEdAt0nfsL03IjDhcqVhcZU9dWYdjCLYHKXEx3RJHy2qzyuEUghBQJS7c6b5nNh/uFxZt2By5DZTzSoQlsZaXYLJjjVi4TQkhPpjP4eR7qcrMgW8h+llV4UjALIf4H4J8AeiN97+cAKAewJ4BVAO4E8GSoEhJCCCEx8fzU4lEgu8E6Vpm7cVc8ghBCCMkbFXWtqKjbEWkdlQ1tkZbv1UK6yPTLhBBCYqQts0smH4bDbqyTqxqj7VOjopfbjEKIvwC4BcCzAH4OQ78tpawH8AGAX4ctICGEEEKCI4GcUVORLo4TQggpMJZHHHQokfTmIkMUmwkzIYSQ2GjtSOatLjcLpu/MD7bLNC5cK5gBXAdgpJTy7wBKbNKXATguDKEIIYQQEi4piw9mQgghpFjwGlSX6mVCCCFu+dKn9818in6yVKzuL9zgRcH8ZQATFOlVAIJFCyKEEEJIJFh9MANAbUtHTNIQQggh7vHsIoMaZkIIIS7Zb8++eaurprn7hq3zomBuBbCPIv0LAGoDSUMIIYSQSJA2Fsy7m7rvAIcQQkj3wbsFMzXMhBBC3JFPq+J5G2vyVle+8aJgng/gfLsEIcSeAC4FMCsMoQghhBASLhJpJbMRrxN2QgghJA68+2COSBBCCCHdjuwumXwE+Vu1vT76SmLCi4L5EQCnCCHeBPCNzLHPCCHOBDAVwJEAHg1XPEIIIYSEgswdNHVnH2CEEEK6D1wQJYQQEhVZBfOGqsaYJSlu+rjNKKWcKIS4FsBTAC7OHH4z8387gKullHNClo8QQgghIZAO8meeoG+s5iCKEEJI4fPCtA2e8tOCmRBCiFs2Vjdi7IodWFC+O25RihrXCmYAkFK+KIT4AMBFAL6CdIDe9QCGSSm3RSAfIYQQQkIgKSU6LFuMO5K0CCOEEFL4rKzwtqVYUMNMCCHEJe/M34K53dg3cr7wpGAGACnlDgDPRCALIYQQQiKitSOFR8evi1sMQgghhBBCCCkoDtirb9wiFD1efDATQkhsHHHAnvjsgXvFLQYhhBBCCClwrEFtCSHh88NjD4lbBEJCY1ttS9wiFD2OFsxCiFd9lCellFcGkIcQQmyRAI4/fD9tw3/ZKV/AG3M25UcoQgghPY5+fXqhPZHSZySExAb1y4REz5tXfhdH3fZx3GIQEgpVDW1xi1D0qFxk/NlHeRIAFcyEdFM+d9Be2FITz8peOrKr3p/ev352XGwK5ht/eiyenrQ+lroJIYTkh1HX/QC/fHpG3GIQQhRYg9oSQsLlwL3pToAQYsbRRYaUspePv975FJ6kue60Y+IWgXRzzjvxCIy6/geYcetPsP+enl23h8Jff3yMq4jgB+zdF1NuPi1yeaysuf8X+OfPvpz3egkhhOQXCf+KqzO++mnccuZxIUpDCLEjbZhACImK2bf9BABwyL57RFL+0384KZJyCSHRURQ+mIUQg4UQUvH32Uy+qQ7p79qUuYcQ4n9CiAohRIsQYq4Q4qcO9X9fCDFTCNEshNghhHhKCLF31Nftlm99/lNxi0C6OQMu+AZO/NyBAIA7f3V83uv/2hH748/fP0qbb9hfTgEAHH3IPhFLlMuefbm+RkhPZ+7ttsMIUoS8dNnJjmlBDCPvOvt4XH/6l1z1aYQQ/2T1y0Ou+m68ghDSTdm7X9roaMxNP4yk/O8cdRAG/OYEHH3IPujdy4WVESEkdkJTMAsh9hZCfDGs8iwMAnCp5e8yAM0AVkkptxnybrbJO9CmzMEA/gHgLQA3AUgBGCOEOMWYSQhxIoBJAPYE8E8ALwP4C4ChoVxZCLix6iQkCMZn7KKTj8S3v2Be1Bh8+f9FWv93jj4IvXoJ9Ovt3GQJkc6XZdCl3w5Vhu8fc7CrfAvvPCPUegkhxcO+Me3wIPllvwC/c1Y5fdfZ+V+sJaQnkQ3y9/0vHYIrTz06ZmkI6b4cup93C+ZjDtUbA+23Zx/8/jufx5SbT8PXj9jfj2iEFA33nfu1uEUIBaWCWQjRLoT4veH7fkKID4QQJ9hkPx9AJM5HpZRzpJRvGf8AlAHYG8Dbluy7rXmllDONGYQQ3wHwewC3SilvlVK+COAnSCun/2cp7yEAuwCcJqV8QUp5J4AbAJwthPhJ+FfrHZ2C+eafc9s+CQ8hBL582L6mY589cK/A5Z5+3KGYcevptmnZCfltZ33F8XyrRdmZX/tMYJmMXPMjd+tnQbaJ/emUL/g+lxCSP/5+xrG2x2lg0z04aJ9+OMVhUfGmnx6LLxzsf5dMtqvq3Uvgm5mdQYSQ8DnCMDalP2ZCCosJ//ixMv2h80/APnt0LebyDSbdnctOOSpuEUJBZ8Hcx5KnH4CzARwamUTuuRjptmaINUEI0UcIsW/uKZ1cCKADaWtkAICUshXAKwBOFUIcnilnfwA/A/CGlLLRcP4bABoB/DboRQDAfntEa/F07omfjbT8IJzyRXdWoSQYd519PN660n6L4KR/qTt4e8xaFDed/sc3nqpMlwA+d9DeePjCb+SmZSYGnztobzx60TfdCumLUdf/IOfY3v1648dfPhS3nHkcnvhdbv1fONi9x5wLvnWkY9q9534dV/+QVjaEFDq/+Lr9ApZwEYiUFD5Tbj4N+zqMzf6R8bV//3lf91W2pKKLkMiZdstpJuVUiv6YCSkoemlW5H/9zcNN31WLRB/eoJ5jEkK8840jD/B1XlH4YLYihOiLtHJ3tpSy3JL8VQBNABoy/pX/I4SwXudJANZYlMYAMB9pzdmJme8nIK1kX2jMJKVsB7AkU46dfLWqPwCmX+usE4JZWqZSgU4Phaf/cBI+d5B3K9YhV9MvWj648tSjceqxh9imHe3CEks3H5YSGHHtKTj3xCNst0k9/ttv4mtHHIDffMt5sSMbjOWCbx2Z447CWL0XC8H+v8ndbHHGVw9zzD/kqu92+po28t5fT4EQAtef/iWcf1KugnjoNafkHHPiwfPVSok7YvBxTQjxhpMimS6rwsNJwZsP+rjoaC79nr8dJ8Wu56IfTFIMWHcZFPt7R4hfyvr/EmX9f+nr3KgUt0/+7kRtnl6WAZXTXHTYX07BCUcegHO+eUQIkhFCsvgNSF2UCmYAZwI4GLnuMTYAeBBp9xd/BrAs8/05S77DAWy3KTd77AhDPijyFkRLVghjpv876lMYeV2u5acTY//+Qyy+62cQnI1HzpSbT7P9nMXNT2CdUFrP+dxBe+HbXzgIT/3+JNOWxCy/PCH9Kt13rrNy9bcnf66zrrt/bfZBZBxUeJnc/uE7nzd9/+P3Po9HbCykAWDDQ7/E97+Uq4Q/bP898LUj1Ct4nzlgT2X6Rd8+EledejTuP+/rtsEAbz/rK1hwh3/fzX/5cVTu7wkhTgy8OHeNmV1aeKy498zY6o52XGUoPYA183579MFJnz/Q9/nPXfIt3PRTe1cvKvbfsw8uozsnUmQkPb5r159+TESSEJI//vPLr0AIoZ1vn36c/eb0rxy+H/YKOYj5zH+fjvNO0u+utopsF2T+ljOPM8XfcWKPPnqVl90OWkJ6Mn53ZRargvlipF1cDDMelFJeKaW8T0o5Ukr5upTyFwDeA3CNEMKogt8LQJtNua2GdOP/TnltTXallAeq/gDUGfMH3VL7qb37OqY9fIF9Y3nEAXu6stBxwx+/93kcfsBeWt+z/Xr3Qr8+vfDMH07CVz6zPw7ap18o9RM1Rx+yj+3nLEKITjctt/4id6XqrSu/i76K4Hpzbv9JZxRhAPiRxVJ6ys2ndSpV992jj+1q2J9O+QLO/sbhOcezSMOE/Bf/396dx8dV1f0D/5yZyb7vSZMmaZY2bdomTdOkSds0S/eVUloK3Te6UkpLacvWAqIgiwKigCiLiMiOiqAsoiyiIoLLIz4+Kuoj+nMFRfQR6Pn9MTPJvXfOXebOTGYm/bxfr77SzHpnMnPPvd/zPd/vxHKUKrKkp9fZH2BcvnxiyIx4UCyzsq5aORkXLZlgmvG2Y3a9qwYZQW6CBETknhDAksmhc8wskTEypDs4GXUr0goZOWk+TK7KwxfOmo7esaXK24wuzMBCkzIugH+8WzSpAv1N6vtbkWAWMyWfcEvT9DQmQjVIosic1eNsouSmtW0hl503byxSvB7ctbUDN68LbZyummS38/rlC1BV4KysoPF8rau+CJu6a3WXTasdOvdTfcOPLGzCreun4kfH52PLDPMShGOKs6IWF6GT00WLx8d7EyzZlSpVcZs0k3QB5kBt5eUAvial/IuDu1wLf9kLbfewfwFQRXPSNddrf5rd9l+Ky4fd1JoCbJ5Ri719DSHXrZ42OuSyZS2j8OLRgcGs0kh96BRVz8dQZ/XU4cfH52Mpl7C4tq8/9G8cDd+5cADfvWAAu3tDH9+stEZQRZ5+nmVPXwPKc4cyetNT9LuZrTPHoLpw6OCivaYAx5Y262bXjTu0GfVD25Dm8+KJ/T0h23HDGvsDHacZ83dsnmZ5/Zf2Os/WB+zrjBkZS4Q8sLNLV6/c+J5qg1rJmlm2tGUULljUhMfPmYXr17TGe3MSGut0x1/wG1dVoN//8fwk9pxMJkbi+cN98AUmVSsMq1PyMswn9J3KjLD0x5FFTfjS3pmYWGm+siYjxYsbz5iC5lG5ET2XyokTEnsUx5tEiSzccoLhHrdZ4SozitSpDjJ+o21vvz95ZVptobLvhHGS/ZRW6/P7lqq8kFWcDaX+lllfOdtZ8KvIkJymrcusqtFcmJmKec3lSPV5kJ1uPvbetaUj4hVokyzGZBr5msojO9663Sb2EKnxLrbP7VfCSYB5kRDigBDiAIBd8E8QrQpeprnOXXGf8J0CIBOh5THM/DbwU3tG8nsMlb/QCl72puZ2sLjtm4rLwxbpDk0If0mB80zqpBh3uMHni1aA2UrHmELs7q3H1JoC7Jhdh9QYZQXNGV+Kslz3GaDJYltPbA5SM1N9KM21LvOgZfWRTU/xYrtmO40z0OkpXly8ZGiZ07GlzZYH8vOby0IObIw3f+2Seabbf9uGdjSWZuML26cDcLZMsnecdVbX5Kr8wf9HskTZzKc3tOt+b68t1NUrXzJ5lG7FQHqKB5WB0iR7+xrwxbOmR32bYq00Jw1n9dRjfEXuiC+d8/g5syK6v91qkWg5d87YYXkeNzodLIkM1y3rp4a9LPr2TfoDwpH+2R0OiydX4MYzzCcM9/ZFZ8XG188Nnahc2Valy66617AvffKA/j6LwuyhsX9O4+C+GnBXimO6g+bIUgI+ryck2ysaJPz7IHcNgoniI9wSGdyTUyK5dnX4Dc7XKJLMzBjP1TJTQ8ti2JXKuNJk1XSQ6hv44K5ufPNQLyZW5oU0FFOtODU+hu5rrXgCaTPKeoQ/q3p0ofNm7WY+s6nd/kY0YkV6+N9nE3uIxPVrWt1NmsYwg/lMANcE/l0WeKodmsuC/85wtwlhWwvgHQBfcnj7YKTrT5rLXgXQFMiG1gpGcF4L/PwxgPcB6PYYQohU+BsBvupwG+LKGIwIflbmN5fh9s3TlHV5o+Xe7dNx/oImPLirGznpkWf+mBPK2r8jjd33fN4E8wZ2TpmVVdGyq0msXYoY6Q53acuokKCN9vdD88chz6JMzJwJZXjywGx0BbKCozXJ8YXt07FiSiU+qVhWZsfuPc5SZLhpX7OU+iC7EALPnDd7MNDeWVeEjtrYZvlFm/YgcaSf2EW6RH646u5Pqy0YpmcK3+e2Rr9B7PzmcssmoFqVgczlxrIctGgag54sGczT6woxviL62bEAcNOZbZYrnZyMKfsclA0qU0xKXrNKv2+uKcrSHUOV5ujvY3VCrfos7OuPLDh+wxlTUF8ydOhqdvJst49wWi5AOYEauGt9SbarJdJE8XAizC5/4Ry71peYN8suzUlLjGY5J7GtM5N/1ZfZ5PXlp5j3trG6zshYo/jLiozir9okR6SneHUrWI1Uw05eRspgQ07jxLLqJRsfY2zZ0Hi4qzc0QcCubNmevobBrOpwVzkYmZVgpJPDuPKceG/CoBSv/rO4vNW/AmJAURbtpjPN4xixqsHcF+a/fldb4ZAQogTAHAAPSynfNVyXK4RIM1zmBXABgBMAntJc9QCAFADbNLdNA7AZwAtSyjcBQEr5duB+6w3B6PUAsuGv7xyF1xWNR/FTHeRkpfl0mTrBQUoIgb5xpRhTnIUXjvSbLk958Ug/HtzVjStWOB+ogpzMlkQnwC0ddaRNdqoDjGtWDc1qnzOnET/70IKInmP1tNG6AVtlVXsV9g00hmTvqXhtPuBuPv+RBHGy03ymjf7C0VVfhI+d3hpSIgQArjzVumyMqnSN0brp/gaFweVjWlIRVkjzeS0D7XYe3t1tef22mWNiOhmlWto2UtllVNjef5jeqmguEY42N5u2QrPENNWkrrxdBvK+/gY8f7hPV3c+nPuPBJefMhG3b+qIyn7UDSfv8IG51tn3j+yZoSx3ofr7WbQgQG56SkhJo3u2d+K58/vwy48sRnG2fjmv8eHD/S5PNJS8sIuZmV0dvJ9dVqeq7qb2HouHYSUcUTSEe4zhdF9empOGr5w9C2s7q3HhotAanHdt7WB8OY5WTKnERYvHo70mcSfMI2H1KbXqnxP02L6ZeOnogO7z7vMI3URmkKqPj9F7HwxFaY2rhOyOfWuKsnB6+9D5kTqDeegxvnL2TBRpJoAnVuaFJPBoyzyq3ivtbiHS85B4Hf3FohQWha84Ow0P7rI+lx4uE0bloUkR8L5lfegxnbZfxzcP9equM34Fg7EJO5Z7HinlN8P95+hZ3TsdgA/q8hhtAH4lhLhWCLFLCHEIwEsAFgK4Wkr5K83r+g78weGPCiGuEkKcBeAZADUADhse90IAJQCeFULsFEJ8CMAnADwupXwKURG9XdIje9S1YceWDX3IVk2tCrm+Mj/DtJ7fqPwMTK0pwNrO2NR2HVOcFZXAVU1RVki9xJFG9UmpLRpa1pPm8yLNZ72EybjkV8WYpWWU4vXgwNyx6HPQIMjNjK620YLTIEA4VrWP1pXpUJ1ER2JNh7MdsJULF03A9WtadeUugsGKDV21tvevyA/vu2CXjdgbmIyKlfc1qQMjPUaXLLH0SLIxVA1Do8lqHzDLpG689h7fv3iO7W1UDswbF9Kg5v0PIkx7MbjBojxEvM1vLsP66TXIUCyfHS525ZyeOuAv3XDNqhblATYAtAayzp1MnIf7fZ1WWzi43NYYAI507DI+nllWpl2GcrDZrt3t1Cfk2hVKI3xnHQWxyvRPFqcpzjniIcwEZsdnZqk+DzJSvbhixSQsMjSr7hlbEnFdTorMhCQvu1aWm4ajC5tMr68tcn9cfmDuWDSPykN54Nx5/5xGpHo9uGNzh+vH/HAgwWahoiG73cSvkV1AWDW+axumX7+m1XZ1szZgHckK17Nj1CPJiUQuZxcpVcZtIjM75hx2UirP4XyKSSePR+C1Y/PwwpF+1BRlDZ6DnDtnbEhZnBPS2Tl6sjX5Wwvgj9BnIwf9GsALAFYCuA7AcfgzlzdJKY8obr8BwPWBnzfAn9G8SEr5gvZGUspX4M+a/j8AHwOwHcCnAayK/OX4RXPcsypD8f2L5uDLe2eiu8G8advdWzsxe2yJaXaXHbdfrDHFWVEp77BshDcQPCEl5hrep6k1BdjYVYMtM8Yos12NptcV4bpALa+pJjP6kWZYaqmyIO1OascUZ2HO+DJ01BYq601GI7Fy68wxeOPKxXjt2Dxl84pYCzaqMKsdnpHqxfLWSt3s/LfO78O3DvUNBkesbLbolmz0vQvnhDTeMLL7TIRT601lpsV+SStWjS6Hy7iynIgDDtH8flqJZGyym+yLpFv3ladOMj35rynKxOe2dionUrV3Mhsr3bzmYNZa8DMcrPfu1qgEnijV7rojmSg5urBJV1c+HA2l2bhseTMuX95sej3gD2ypGsJqre2sGfysmH1mZzWWWD6GcX+sfV8+CDeqZcOYYTWv2fq4aaHJ2HZWoE9CruJ7kOrzoGNMoenEa5LMjyWEKdX5yE6L32RMItCusounsGswOxwMnJT3clqShqJvuI6XYiHFK/CdC+Zgx2zz3hAzGopweEGTo/M/I2Mpqf1zxuKHx+dZNnc3m8APmt9cjpeODuCmM9uQl5GCnrElqC3KxNfP7UF/U3jn+aqvoPbY0as6v9T8vZ0E37VfzYUTK1BnUe7GysF548KexIoWrzd5J1DsHFowDq8dmxfvzXAsUcqkSAAek1Bez9jQY9q8jJTB/iDLWkbhtWPzcM6cRkyqzEOHpudNRW76YAzJWIZDK6kCzFLKLillmZTyA8V1v5JSrpJS1kopM6SUWVLKTinlnSaP9W8p5SEpZYWUMl1K2WGWkSylfF5KOSPwuGVSyn1Syn9G+/VZuTYKB2hF2WmYZCigbzSzsRh3bunAF87yn/gZG9gYg0jG5WBu6tEGXWdT4uLJc3tcBaGHK3vix5fOx8EwZ2edCNazSvV5kJnqw6cM77EQApcun4hLlg5l5GbbdKlfMaUST+yfhc9vU5/gnz+/CUIAveOsT6zNaHewqgMAO0II3LaxHfft7FIu8UrzeVEQKAfhdhuDVBnSAAZrgH7EptyFW/ft7MKSyRX4VBjZ05mpPlQXOWtE0To6Hz86Pg+3b56GNptGhCU59k3j7M6P2qrdLz/sqivC/GZnQf7dfQ3IsegEnch+fsVCfPWcWa6+E8lkZZt6nzuxMhe7e+tx+6ZppvseJ9Z0VJsGgh/Z7V/Fc7Uie9VJLTE39ca6G4rx0tEB3BHoAN1VX4Qv7zXviG41ETtnfGlE36VYc3L+5KTb/Y7Z9eiuDz1R1a4ssbKhqxbrHazkAIAPr7Deh1+6vBnXrGrBoyYrwC5ZOgG7e+tNr9/d14A+zTikPQG2a6YcbvDDuOuYXJWPjypKlWwKTDDmpKfguxcM6K6b1Vg8OK42luVg/xx9kKGhJBv37egynXi1K3sVTdPrkquXgJHZuHnNqhZ8aa/68+TExq4avHbJvJC6qWQu7BrMAL68dyY2dNXgpaMDjrIEQ0vgyMDPsJ46aSRMtp4F1SRaorl7ayeeUTRNdfK5EUJgV2/94ModK08dsJ5wBWCbbPKx01uxt68BTyqa5AaV56XD4xEQQuDOQK8n7Upqp1STPBu6a1GRl46BplLl9do6yiHfR5vnS/V58PAu9/vlSCaS7FaIbrFIGrJL6Ngxuw5rO61X1uZlpESUhX3r+qnK8guR8giBvIwUPLCzCzMainSrthOR2eFROCuArVYsOOXv1aTemJsc9M4IxkY8HoH7dnThsuXNWDK5Attm1WHFlCo8f7jPsuknj0wSgLEJn1HzqFysnFrl+MQrGqbWFOLVS+aGFP4+tlSfMbS9p073e11JtuNMRKPsNJ8ys2/J5Ar88sOL0FiWY/rF1c6uGI3KS484COlEdpoPW2dFv5HESxcM4NtH+/HdCwbg9Qj4vB7U2eyoPrm2DRkpXlywSL2TEkKgqTzX9ECiZXQ+Xr5wDj6z0b7GssopUyqRl5GCtup8ZMVgKbXXI/ClvTPxyJ4Ztg0H3frY6ha8cKQ/7Bl3p/wNktpcB5PWOShZk5Oegr5xpXhgp7OaUMHA0OXLmzHfkBlnNziGmx2kZWzk2N9UinyTetLpKV7cHYMGb9GytGWU6QFQitcTleBymU0Jm2hx+ye9YsVE5X3LctJx/oIm9DWVKpdphcMsu6wga6jm7aOGAE5w+WcwA0f1mXYbOyvPS9e9JrPJ3K+f22OZVXvbxmkJXfva7jMxtiwbV502GZNMSm4BQI5mAtTYfMn4+2UmWcpmji0NPU46s7Mar1w8d3BSw7hqJDPVh9OmVpmW3sjLSMH5C5p0zRy1stN8uH1zB549rxevXDxX9/e7aHFoTVYt1Wqx2za0m+5DVMt9je91U3kO1mrKNNmVM9lvCJzZ1aG82XASGcv+F3dtsd7X3xPBRNVwMHsnc9J9mFyVj59cOt/14+ZlpuDbRwdsb0t+buqrTqrKw2XLJ6I8Lx07e+vQUVsYsjrGSVBp4aTor5ITAnFv5pwo2elmirNTsaLNfsIz3mY2FqNYkegR7XmJhtLIJwSKs9Nw3vxxaHQYMBZChFWixO6meRkpeP5wP27b2K68XvueGRMGVJNMxkvsJn1fOBLabizYtyiSv5fZ6wk6xzARrNVUnovDC5pweIH6nP/owvG4YsUkfOcC8/HitWPzcHCe+9J2NUVZjhOFwhE8nGqvLcTnt03HlARNwHg80ADT7PO7brrzMrNWKxacmtVYbLraOSc9xVFimdaGrlp84sy2weNJY6lAIwaY48zrEdjRU4cZDUXY1F2rvM09geW2w90FNz8zNWRQyEj1orrQ+kPVM9ZdgNnMxu5ayxPustw0y3IAJyTwsdWtODh3rOkMYElOGu7Z1hlxpngkSyOqCjJMM6Qq8jKQnzkUOLltYztObx+NJ/arO/r2jC3Bj47Pw1k97ndSRdlproNhhVmpeOnoAB7Y2a08sNA2yHL7lo0uzHRUKsItn9czuFzEjeBsq13zPLe2zKzF4QVNIU00VIzv8XPn9ylvd82qFnzrUB/Wd9VioiZw/6m1bYM1Rc2Wpb9vkx00xSKL2th5NzPVZ7qNQGSlGz67qT2iRpipXg8yLQI2N54xBc8eMt/2SC1oLscpDjJE42V0YQbSU7zKpYLRbuS4Y3ad5fXGevSjCzPxg0vm4s5AfcHH9plnGceKmyyeWLhudYvLFTfWf8PNM8YgxevRragx0gb+tRPnqgNeJ/Xmjc+vUpiVihkNxfjiWdPx0G73GUpWaouzUJilb+qXleYbrHescuXK0OxjCeDes7pCLv/moV7T5pJas8eV6I6ZjGPwZJuVbMZt0WoszcYMQxKBcX/UOaYw5H1wy2oJJqCfUEpE0+sKlasigokYWWk+XVMrp4K70sKsVHzCQTZSvJgFPKJtZVuVbRafcUx67ZLwll2n+by4b2cXrjacJ1gFtIIrKKfWFEZ9Ndz48ty496vIslktGW8P7uoePA6IdRK5m++xlmo1wnCuFkkmXo950FrfI0B/neoY1HiR3UKHCsVEdDAZyzjuFYUxPtUVZ5mu/gP8gXWrzNZdvfXY1Wt9zl9m07/CreWtowaD7G59/dwek/M+YfHbELtkzVgLJkiaxYHsvsnfcnjeaBYLzEnzoSTH32Tw8IIm7BtoxPkLmrCpuxZ3bnFfU90tBpjj7K4tHchK8+Hz26bj+LLmkPIHgPkSfkBdkiJYc295a2zqEdvN7m3qHoNjSye4Wv6nygTQ1jBUxSe2z6qz7JR7QkoUZKXi7IFGTKsNnfl6YGcXvnfhHHQ3FEdcG9XsWODMzmq8eKQf/3PFQuX1P7l0Pp4/3G+aIWVUV+LPErNqHhJphmCkMlK9phMD7bUFGFOchSnV+RiXIAGXaIv1bGtOegp29dY7ClhpD8Q2dddidGEmTlVkdXg8YrAER77mwKh//FCThXXTa5Qdi8dbLJXcP6cRD5l01j04d6yyFrjdMj2tVVOrQpZqfvfC0Jn6z25qR39TmW0jTDNluWl45ZK5+N6F6gZxVvqisIrinm2duHn9VNOJnxeP9ONIFJZWRYNqX751pjYg7O50TzuuHV1onR2qkpXmG9wvOQnWxcpwTxhrtY7Ox6ltVa7+AtqTL+OxQGlO2uBJ9tTqAmVd9owUL+oM3elXBAKUqlIP0dZZVxTRxKEbW2eOwaqpVbha8frGluXg0mX6STspJcrz0kMaDtWY1JMMOe4wNhY0XL23zzwTyk6uxfFo0M3rpmK3zYmuEzevm2qb+RbpnFWji7qlgP3J4EdPm4z9cxqxf2BsyOqe587v0wXm3NSIjfZknUqkfVHeuHKxbcAjWiSkbeksY/ZiTroPH14xKeIyDydMAlqLJpXr+sK0m/Q8MdOl6D+iJRH/ep9jirNMk6OGk9nkgt3X5LObrLNGwzHb5TFe8LwvzecNWZHRakjMuHmd/px/gUXGqNkx563rp6KxNFvXQDyRRLpv0034GL4eXfWh3ymnJfc2ddfigZ1dIY85uSpvMAEnxevRTVzVl2ZbxnC0hBC4drV1kls0MltVrCbBnbh+zRRHWepmx143r2vD2LIcjC7MDElGcprndmDuWHzoFPumzbFmtrlVBdbHnU7LXx6cp04M+c6FA3ju/D5MrSnArt56pKd4kZ3mw/FlzZitqLkcbsmocDHAHEelOWkhmSALber1Ganq+127ugW3b56GqxSZMdEwptj6gDzV58HmGWMwuSo/7Mde3hoa9NLOStllSapo7zFnQpmunMbazmq0a5aYTRiV6+qAeHW7f9bRrH7nh1dMwqj8DNOgb6JnAURbeooXTx+YjYd2dcc9EH6y6XPYkXfFlEpMqszD2s5qXUBWCIFPb9AflG+fNUb3PTKaVJlnevCx0qRGuurEKVjjVvU9u2X9VPQ3lWJ56yh8bX8PSg1lJHweoSt38ojJagErT5zTg+w0n+n39f6doVmHQcb3zMrxpRPw8dNbUW9oNqJt0LqhK3S5VWlOGnbG6ADUqeC5gfEkYeHEcsvGMU5dfVp4q0yCWc7Xr2l1dHurY2SnGQZO2JVOsDOrsdh1cMyqblokZjQUDwbvPR6BcxUZ0qqTx2tXteDli+agb5z9vinZOooD/vHu6lUtWGWS4WaciA0eo+zQlCALZym6VVbvRYvHK0tmaLPvtCfhxj+X3bleaU4aCrJCV7+54aT5bm1xZkQNZu92UWLj+NIJqC7KtKx/3FZdgP1zxiIj1Ysaw6o/Y48Mu3iKqpSPkyPhSOszlydws1EVu/fRuO8Rwp/88cT+nrAz7rX7IW3jbe2nvru+WPc9CPc7kZvhs8zKllJi9bTh6TFj5fiy8MoYxcJNa9uUzXHtVmGmu0w2MCrOTnX0PVYFdT+jKY3QbYgJ3LBGvzphwcSKwYmfgabSkIBksHzLqW2V+JhJ6aJ5zeV48sBsdNpMYMSL3dJ7O/qmm/q//6zGkpCVb8YJkoLMFMxo0L83KV6B48ua0V5bGPI9NjbyzdOU9/MKEZUGn9GYsLWyp89Z7eXjFivTnNjUXavMNK4vMT+WNb7fqmPIrroirJk2Gmd2VNuWDTIeSxnLQTr1oEnSlNmk39wJZdjRUxd22Tcjn0nnvsxUX1iJWcEGn7Gqo8/IThyZZd22aJYv2i35UslM9aFvXGlYH7RwXHnqJPSMLXF8wh6OLTNrdUGVcwYadZ1xDyhOWO0O2rQzZileDz67aaiu8GhFuQ9jwxsAmD22BGd0mJ/EBJsIRaN0plUh/5HEY7HEiaLvqQOzcduGdvQEgnx2dbyz03z48tkzcYWiQdao/Ax87PShQfq0qZEtDVQxfpc6xxSi1yIAVVOUhc9umobr10wJKbkBAHdt1S8RclNeRRu4MR4k3bF5GqZpDmyM+0fjRIpVkK+pIhenTKlEqsXJz4WLx4csH4/298l4YOxkn18TmIWvyNPP1hs7nL/3QfgH3T6PCMnqtHNkQRNeuXiucvISGArCBBthWjX5c5phYEa7XDzSv1UkmYF9Tf5sBlVG3eyxJZZNYnssJgmcnEipbuHxCMfLG68/Q3/Cneg1eMP11X2zBsth7RtoxG0b2vHKxXPDala80VBWJDPVi1mNxagtysSaDnWjn6tOm4x7z5qOPX31yuOsILuPbfB6VbDHLdXkXHDlWWaqz7aJo5lH98wwXTJszBTUCr6Hz5zXi4+eNhnpKaH7JO134ULDZFK4WacrFCWRtMe17yv2pTMaivCzDy20LftmdXLpdCu/f1H4K3piwS7z0fg2affB4QaBbtvYjkf3zMDhBU36lTSaN834iOGeH0hp/zc4pbXSctLNrrFXtLyoqEs7XM4ZaERbdYGyD4hdP4O2MLPKzXxxR5ftSoRH984ICepumTHGdOybVlugnOT51LqpePFIPz6zaVpIssPVq1rw3x9aiOtWt+rKKiaT7bPqcOqUSly10m1JGeu/w7wJQxOXd2wOfQ+FECF9XhZMNE/+K1eMIcHje6d1d1X7eK3zwyg1FMvGuG5LUt28rg17+xqw0WS1g77MkJ7xK6w6dRgYXwqPR8DjEehuMJ846W8qDZl4dTuhMdokI1k1vLeOzocQAkcXjQ+77FvQofnj8JmN7WGfA5lZP70G9+3oskyMigQDzAno89un49JlzVjaMioku8Ks/ulwGpWfgbu2dJiesEcizefFak0mzeYZtbrrJ1bmhZxMaA8Mjfud4uzUkOwWu4M848F/XXEW7tzSYdnsLRg8isZyNavalURuNZRmY86EssGTqk0zxmB56yh81OVKB20gLvidMutAHPxaqJZhmWWYGANwPk0wNdza4OMrctFd7zx79ruKRhjGuqVfOVtfv9cY/LbbP371HHX99LWd1egMZDBq923GQFqaz4ueRv2yp+C7oloOFak100ZjeWslnjk4G6e2VeJyk6VowQzjWY3FWDd96OTW+Pe0CmyYZWu4yQMRQlhmp331nFnY01c/2LgslnNexqDwdkNTWGOpBDNn9dSZfp4Pzh2L/XMasa+/Qdkvoa4kC9sCpUq6G4pD6jCPKc4KmQwISvEKrNccHLtKzHFxn7P7G+AR/kCjMfhtzPhKRtqPXHHO0Gc1xevBnAllYWVXfnJtW0iGshACd23pwDMHey0nD6bXFeHQ/CbkpA9lYJXkpOnqSNqVFwqOC/Oby7Gpu9ZlnW+9uYpSDe21hYM1u62CSFbPb5XAsWBiBV67ZB4e3BV68hUcfyrzM7C6fbTyPdF+zIuy03DhoqEgpDEBya5Bripwqi2xU1cSOlkcXA2wYkol+k0CkDtm15mWN7htQ7vjSbCiONe+BABI+/2Rdjz9xnm9xruHRQiBltH52NVbrwtQ6SYoDRtkPD9QJbMYt+k8i6XrJ6SEEMJ0LAaAK1ZMwv07u2xX3xjPtcKlaj4KhGaHxsL4Cv+xhGqBa4FJs2jAvyLJSSLWTWe24ZNr20yPWR7e3Y36kmzl5y/Y7Pye7Z3ITQ/dlvMXmP99l7aoy1x6PcL0/QYQtQBUvGSkenHd6a04fZq7yZH/aCKQqhr+DZpsWbMm8UII3HDGFLTXFGDn7HrL0guqJJxnD/Xinm2dWOSwuWc0m2V+zqYJejzKUvY1leK8+eNMP5va707oxJz+b7hOMWm2ZPLQd8VY+mHuhDK8dsk8XL+mFdevaY15LXbVuGm3grU42/4Yb09fAwbGR1a2SsvjEegYU6g73oum5N4LjVDZaT5s7K7FjWdMCVk2sN7lzEeyUp04hHOydfnyiSGZg9oDQNUBgXFnJgdva79bUm2vmyx0oljLTvPh+jVTsDqC5cVBwQHVLPOtMdC5eufsejy0uxvHNJMoTidltBnH4ytysHiy83JC4WYOlSoyEu7YrM+AjnT58JjiLOUS5suWT1QeoKgCado9UmFW6mBw9CZFbf5w5Rrq0gVPdupKsnHd6lasn14TMtm3deaYwRMfIQQOzh06eTK+ovzMVHzzUG/I837zUC/OmzcOcxQHUjedaf26nBykGdWXZOPQ/KbBkiqq5eixcnhBk+6zaZbdYRRceaMakVpG52P/nLE4MG+crhxU0LrOGt04tcRwEluWm44bDVnCQZtnjNFN7tidnKu+dm7qzR6cNw6vHZunDDSOOC7OfrRLdM3KIgghbLP5VLwegReO9GOgqRSZqV5dU0aViZX+E3aPx7+k+OwB6yDarYGJHaNoLdtcaHGCb/ZWTwq8hrzMFEytCf0OGccsVW8P4+HidE3morH2u1XQ/pb1U0MCZ9evadV99yZX5euWLpfkpA3uSzweYTrxe3h+E5a3ViLHMOlQnJ2KORPKHGV3WgU3h5OEfQaz9nrjfj5a9Si1Hw27QInVahnAf86xYkolvra/B1cqGgQGN3lUfoZlz5tptYWoNMm2m1ZbgONLJ+DYUuvJTdV47MTxZc24b0dsMuSCguOhcRsf3NVt2WchM80+uLy6vQqLJ1dg0aQKZXm5tZ3Vg31WVJ+ga1e14KHdM5QTwqe2VSrH0KcPzsb1a1qxttNZ9ivpaccO1bF8XmYKnj44G0+e26NsLBy0rGUUHtjVjSMLm0zrKJ/ePlp5LlCWm47uBn+JnHmaOtndihrQQPhJM1aMq+M/b0hOuc8mY9WqNreUUPYKs6PdNav200WaY3djyRGjzroiXbLSHZun6f4Gxr5HO2fXIy8zxT/Wpafg/Q9OhLv5poLnHFYrRVJ9HsvPGQA8tCuyxtNf2J549dQZYI6jvSYHfTTESQdd1QASCeN+PrgzdHr4aZyJNO7ciUaa4HdGCKEL8n12Uzs+u6l98ATA6xFoqy7AqvbRKM9NR1t1vmVQ8KHd3ThtahV29dbrGlMJIfAJkyCYiipzxKgyPwNZqV5cscJ/wmzM4gy3RiPgL+kQjq+cPdP1geYLh/sHA9PZab6wulerPLirWxfYUG2VMbBiPG60mzwwNi0ryUlDTVEWPB4RkjEyrizHtiZrNA6y0lO8eOXiucos9nDZlRTxeT2umoAGA2ANirp12j+BKt5iN45tmelvAqpqEGT8a44ty9Yt7TT+vVX19d3GcWKVZZEItFnFboLATeW5mFCRi4bSbMxqjP7qhfQUL27b2I4fHpunLD8E+E86F00qx0cUgTCVjtpCfO/CObqTby2z+oZObZkxBhctHo+G0vAD1Q/vtn5u45/oSsUqoIIs/ed1UlUe7tnWiSfP7QnZx59rksk6uSoP85vLMVHRVNfoNM3Kv7Wd1bogg+o7V1WQAY9HICPVi6fPm627LvhdWzq5Apcvb1buV69f04o3rlyM9SZLwI11LSOtOW+nMCtV9zpVk2snLOIKTpJNnMjSBDSNTcOND+dksk0IgXHlOSGNUQF/vfMg1TJ93eOYXH7/zm5sclCW77aN1hl4VlR/Cy3jarBwXLa8eTAL1ViKps3QLMwYCAy+J5840/xYcpKml5DqfFTbLHu64XV21RVhYLx5+RKz48P6kmwsb62MatDxZDK2LAe3bWjHvWdNNw0M15dkozEKmbylufarNy5cNB67eutxz/ZO3LWlw7IxYywYe33ZNR20qs19QkosnFSBsWVD+yNjosgZijJc2vHImHT3iTOn6MrEnGooF6I6JtJmYRdl6f8GveNKcPVpk7GyrQrnzRsbsh9oN0waC4R/rhb02L5ZuG51Cy5abD7x7uSRVeX3tKuejIwJVqrmlfHGAHOcZKV5XTcmCS45iuaSikRld3w3o6EICzVBBydZCNolM1MVGRrG7MFg0yyny4G1tRLzMlKUB4ZaqjpTwa7CvS67EhMNJ/13Zuj//U1lytIy2Wk+PHe4Dw/s7LZchttWXYBrVrXg8IIm5bJvO4fmj0NtUaZt0CPF68/S+8llCwazRiI56Qm6e1snctN9pll/2pfwwM6uwey/ILsTXO2qCuP7E0k+VnluOhrLctBcOXSC3GzYNiD0bxBywqy52snJuvaE2Vij2hiwMSrITInKCQPgD1ZEY+JyeWtlSCa4Ubgd0w/NHzeYzW/XLEQVwBhvCBBqszluPGOKZTal8e8thNA1ElKdyBhffzQa3ow0iydXYHpdIVa2VTmuRa3l9Qh85eyZ+Pr+npgtjxZCWDbkXTipAp9cO9U2UyfoizumW9420sbHlyydgG2z/KVgtM0Stcw+isbX+dHT9AFk4/egODtN1zvj6tMmhzSZBfyrUFT7qNLcdNy5ZWiFzISKXOSk+3BdoIHX3All2Khp6qoa+zyW+9rQF2rVCEv7POu7apUnr3YloK43NCcL/i1ioXV0PvYNNOr2paqguFUpEnVt+PC3JSPVi89t7cC1q1p0PRkARYBZ6sc8I+1k0fuK6Hg4jdzdln7qri9SljYLl1mpgPt2hB73GFkFgLUlFbPTfLqSHMbvyTFD+cHg9Usmj8ISkxVx2vHKWNt1bWe1boVDaW46HteUPps2JrQhnJbdpAC5N2dCmW7VSLSdM9CInrEljnphFGSl4vCCJnTXF8Pn9QyWYzNjPPd4wCbj2G5lnxtmCTWqmIkxUcT4Pfvafv2kqnGFnHHlwfquWl2mt3olnDkhBFa1j8a1q1uwt78x5DtYXZSpe4+9XoGHbCaVzZTlpuPUtqqQ8y9taR63pVO399SZruQyNv9MRAwwx4lXuG9wdmzpBHzngoGwmr4kE23TFdUXc1T+0PVXn9aimxnLtjmZB/wnDw/t7san1rbZzqyPykvXdFePzYmxqs7UZze246qVk0IO0okSndOaYylej6tsvXDs6WvAs4f6UOui7EE0mqROryvCq5fM09XLNNOu6HycmWq9DbEK1QUDk7npKXj+cB++fbRfmfWgOmHW0gc97J9Xu7/Ly0zBxzXBS7MgSFVg6e+O2bHtsu2W3ThvFWBQma/JfinNTQ+ZvEjRvNGVhjqNK9uqQkqtaLO6tEviVXWYzV7K/Tu7cPny5pBGNV6PwEuGTPBYfGaPLPQ3wAmuPkg2KV4P7j2rC9eudp80EGxwkyysvhfGBkvhetxQ3/7IwibbfamV1e2jbUt2aCdzzGqnWt5fs/O8/JSJeOXiuYPZ1/5Ar/Vyee3+0fjOqoL12lIqVnW5VVSZlcYavqrx89b1U9FUnqOsDe/W65cvwCN7ZiAvI0WXYKLaRqvnVU30+dxEmOEPDK90cH4m4S+91TwqN6TUSEVeum7ZtTGIc0ZHtbJJuVaq5tzI7fnmPdunY0+fs9W2T+xX95UAgBvPUAfB7M7BAH/Jg9cvX6C8zlgSyGp5fWlOuq6UjJZZjV3tx6K7vljXqLddURpH+zcxe8fPXzAOveNKsDOCRr0UX+fOHYu7tnRYlmBxyzjhYjw3MGYMh1MuUEUVXL1rSwcmVOTqAsp3b+0c3A9Z5Qmkp3h1WdrGVU91JdnYq9mnGLOHvR6hSxxUxYG046WbXZv2PR5oKsPkqnxl02u3njs81PRUdVhmPDY3c8fmDmzsqgmZdEiG1Q0MMCchIYRp5+uRYGnLKJzePhqHFzQpD1InV+XjgkVN+NApE0MaHWydOcbRwXJbdQEWTrLfKXfVFw+etLkp2+M2W6soOw2nT6u2XcpClGiOLGzCofnjopIBPFxiOVhbBX3sao2ZNVsLstq9VJnUXAxXVUEmKvKcPdaaDv2qHG025TSTE8mawNKwx/bNDHm9p2gClmYHkV85eybu3tqJ7THIkIv1sm7AX3O7pSpvMEgaZFVT00yKV2Cq5qR3V2+97rOtauSUk56Cpw704LF9M3UHvXv7G0P+Hmaf5Gm1hVjfVav8rBtPwM7ut67J68bO2fX4wcVzWbMyQX3sdOvA+R2bp+l+n9kYWePG0NIEAo/u0X+f0lM8YdVst6u5r90XuxlPtLtyjwitowmLADLgD7TVFmXC6xFY0aaf6Gkqzw357t+gySLLSPXq6uS6GQ3tavgCwLzmcjyxv8fVvk3lwkXjdecIdgsY9/Y1oK44C+fOCe0VoQowWyTsuxLyFFJiwqhcPLZvFtZPr8Fz5/cNXrW+q0aXSV+Zn6HLcjeOh+8rXvwdW/Tfq3DLzkyvsw/+ajWVm5dyieQYS0r1hMXMQI1bLbtgk1fznmqPT/IzU5XJEcZzOG2ZLtWkt5NXubu3AXdsjk1wkpLPsjAnJLWTTVMM5R+cCvbLWdtZjTZFmbaJlXn46jmzBrONhdCXYbBbeWcXu9D201CtjDKOh0ba3Z3bDOGnD87G57d1Dk5yOVlNqI0v5Vk0ENWVPVNs35MHehxtY3leOi5dPtF2lUciYoCZEo7XI3DVaZMtl56c1VOPdYrabznpKXhA0fXbLe1+wUl2tBNPH5xtfyOiJJWZ6sOevoZhHRCtaoZZCQYi9itOOAHg4iUTkObz4DMm9QeDByZdLp8/GBAzOxg7unA8Fk0qx7Um5ZCsDoj2Osw6ioT26c9fMC7kBDPN58XN69pweEETOhQZ2oB/+dwLR/pNu3kHmZUOyM9MxczG4phMEkRjWbdZzdqgstx0PLp35mAppqDJVfn49tH+kNtb1QJ/7vx+XYmLzFSfbvmk2XF4Q2lOyPufl5GCpw7MxkFN4063B/Ja+2LUe6IgwprjFDsrplhnc/aOM69TGqRtVGeWhWilsSxHF+j+zgVzBk9sT2+3L1cXTq6Am++JPiMr9P41RZkYXZiBstw0zFIE4D0egS+fPRPfvWAAVQWhma3aAPCpUypDxmddJqli8+/ZHr1eIvmZqVFZ1r3dUPrErqZxbXEWnjmvF+coal6rgtPR2N/pn0P/JMa/s11QYvbYoZIZxmuNmbwdtYUhjeVUy9ut3LJef9zzjfN6db/fM0z9Zcz+qp/b2hFy2d6+BhRmpWKxSQLRyrZKjCvLwZLJFSHJSF5Fxnqm4TYfaEqVqD4e0f7M0Mj3YYd9C7S+tHcGNnbV4JZ16nIbwWQBsySVs/sb8LX9PbhsufWqr1H5Gfj20X68esk83TG2XXLMefPHoak8B3v61HGcltH5eHh3N144EnqMC+hXX6jKfs1qLEZhViqqCjLQWGadiGOmviRbV9bNSX+QH186H08d6MGLR/oty8lpOUm8cGNUhI3mY43TZzTiaJfBhXtAZaTdL8xqKMaC5nI88ZM/RPSY9SXZOKV1FB559U2cY9NhnSgZxKuu6j3bO/GzP/wDK9us60GauW/HdPzkzb+H1EoM2jpzDDZ01SiyyfxuXT8VT/30j5jrssP6kYVNmFSZF1LbLygvMwWfXGtery3HYtJr7oQyDDSV4unX/+hq25zQ1oWsLVKXIVkw0XqlSHqK13K52L6BRjz66u9wcJ56EiDRXbJkAnbe/X1s7KoN+74VeRnY0VOHW771SwD+WnvGALOuDrdNWRezMiNWts2qw7VP/rf//hGeO7dU5VnW8aWTgzGb2IkDc8filCmVGBNoAurG8pZKZKeloKk8Rzepd+nyZnzx5d9a3tduhNMGD91snr4mcqgUrwfPHOzFf94/YVqf2mkjTDflEozBykg5aXAXrtXto3HjM//j6r7XrGrBvi/8QHdZkYt66FaMh0naesGAfv9q9xkyTqgWZafhosXj8aHHfgoA8HkjD3QaJ77HGEqNGcst2ZlWW4DvvfG3sLfDbFxTfY5Lc9Px3QsGTMeZzFQfvnauOnvw1LZKfPm1N3WXGbNL8zKGxt9GRQNRxpcpHMXZqWGXKAL8CQiTNQ0oje7e1on7X/4tNpgcdwabhzqhWsFYWZCBN/7yrul9SnLS8MR+6yxdqwbXPWNLkOr1rzJSjWtZaT48d34ffF5hen4WLrMRaUJFLk5IiUuX+Sdpw20cPLkqNslWN61tw7Vf/2/sN2kSHG8MMNOIk5nqw4tH+vHeBycibtSkPSH3eASuXd2CJ47ZB5hnNRbjuZ//GefOVQdFrlnVgh2z623r+hGRue764ohOfHPSU2wbgVgdvORnpkZUCz89xeuoVqOZi5dMwE9//w9dXd4gIQSOL2vG06//EZX5GfjdW/9y/Lja5kJW/v3eUIA5PSU2gcMDc8cOLueLh6byHLz+h3+EvYwxaGJlHp4/rM7ScGJvfwN+8Nu3ML2uSFlrTxvY8iqCCtpGarkZ4R/yaU+Y3dbxVD4YnbSCTYy1Di9owlVPvK6ru64lhEC9RcPk6sJM/Oav5ie8gP8YTrs0Nyg9xTv4PXdLG/R18z3RBZhN7p7i9UTtZDreYjEnvau3HiU5aY7HL61lLaNw/8u/xXM//zMAf73RaJeo077ka1a1hKy60H5uzDJh22sK8OM331b2HNg2q24wwKzNdnYq+B2Mlo2GuuG3bZyGlku/Pvi7kzJqazvta00buZ3E7BtXil299fjUs78AADy8uzukNEdJThpuOrMN/37vA0wYZV4ShMiZ2BwTjSnOwvkLmuxv6NLlyyfinHtfxZmdoT2komFUfgaeO9yHjFSv6erESBsBG6kSpdZMG41Llk5wlXF84xlT8Oirv8NHTnXejDUcU6oLcPcwrSJxgwFmGpGMtZndGl+hDwA7PW+4aW0b/uvNv6PTpO6oz+sJqRNIlEy03wXVEiaKvYq8jJBlq1qjCzPx6iVzAQCtlz2pu66mKBO/NslAuMThEvQKzRItVTbPSPC5rZ343Eu/dp0lH6mc9BRdfVQjbdAtVXFiPbWmAHv7GpCZ5lUunbej/Z57IwwQJ0FfEoqTXb31WDu9GrkOs3CN7tzSgWu+/rOQrFCnVrZV4Yqv/tTVfQF/2YlbvvkLVw1lAejuZ1YOKFrsvsbGpktOHZg7Fjc8/XN8dtM029vGYs1TZqrPNGPPiXJNQkqkdcBVynKH/q7K+saaN8UsoHHvWdPxr/c+MM1W/8rZM/HyG3/FGQ4CPxMr9ecgu3rroxpgPr5MX5fbGLB3UkbtihXhlw+IxLTaAnwq8H+zIL9VUzXtXdx+j+jkkawfkbqSbHw5xn12hrvXmDGQ/cT+WZZ15e0sbRll2fB3Y1cN7vz2r5O2ObUdBpiJFG5dPxWv/e9byjrPRsbamQCQ6yAzkiiZzW8uR1N5Diry0h13xKXhl5+Zinf/877ussbSbBRkpSoDzC1VeY6DPGW56fjc1g5IibCzjJJFSU5aXDOo7fQ3leLwgiaMLswwneg5b/4414+vPckeV+6u1t3owgz89q//wi7FWEkU5Da4DPgztiKp67t5Ri3K89LRqsiuBuzLQDWW5eD5w/3It2j8Y6WhNBsfXjEJeRkpUUuQMGMX0xjn8qR630AjdvXWu8qyzs9MwVvvvjf4+2P7ZmLxDc+b3j4r1Vn9y3C4nRxwKjPVh28e6sW/3zuhnOzLzfBhoKkUv3vrXzjVZELT5/Ugx+L9nViZ57j/xW0b7CcCIhHxihcLduWg3NI2c3dTT9mnqeM84LJ0Gp08VrVbr2Dkoq/hc85AIzbd/r3B32N9Xnt8WTN29tY7bqKebBhgJlKY11yOeYpl55mpPpzRMRpf/N5vsbG7Fj2NJcqGK0QjXXqKF4+fMyumJxEUHcbau16PwKH547Dq5m+H3DYvM7xmaW6WI1P0CCEsG+JGKsXrwcdPb8Vv/vqushSLE4/tm4Xf/OVdNHNJ8Ulvhkm9+XjzeT2W2UZORBoYjtVyY6PV09RNDT9x5hQ8/qM/DNaadMNpcNkYsP/U2qk449MvDf4+vjwXU6rz8YPfvKW8/7fO73O9jWY2z6jFL//0T3TVx+4zWmPSqwDw78s/s2kapJQxP64alZeOcosmUb3j1ON6sPyf2XnPladOwpGHfmQ6KXvqlEo89IPfhdSdfepAD+Zc9y2HWw/T5mCROqFrthn+/b0egW8e6sXf3n2PJTTI1OPnzMLTP/1/2GCz4oZnV8Ond1wpvrR3Brbe+TKaR+U67mnglhBixAaXAQaYicL2kVMnx6ymDlEyYXA5ORj/TB4hMK22UNcUaFN3Lb718z/hilNG5nItcu+UKZGVB8lNT3GcVUcj08O7u/Hoq29iT19DvDflpPXdCwbwh7//27Q51JLJo7BkcmRBdjfWTa8OCep6PAIP7erGl157E7/40z8xZ3wpln3ihcHro92AD/AnkFy7uiXqjxuu4TiuMnuOh3d348uv/R57+9Xf02NLJ+D+l/8Xm2bUKq9f01GN+c3lIfWlgy47ZSKm1BSgzxDADrdxlrHZbbRIXbNOd3+HmqIs1CTmPBoliPEVuZZlMjNSvPjXex9gTcfwTDqS3+SqfHzn6AAzx6OAAWYiIqIRzHiiFMxOOrOzGp//zm9QVZCBY0sncMKAiGJiSnWBZdf4RNdWXTDYAC5ZleamR9z4GohObVltAvOWGWOUtxFCYHlrfGrfj3RmQ73d97ShNAdHF423fGyz4DIAZKf5sN6k9OC1q1pw8P7XBn+fM75Ud/2SyRX4yg9/j5z02IUuptYM1cauKRqZZb8o8T11cDae++8/cf8XB55kLYydYBhgJiIiGsGMAYFz5jQC8GdsPXNwNgPLREQWdsyuwwcnJGY0nLwl0SZV5uFHv3sb581zX9M9KEtTIiFYO/7W9VNx9hd+gAsXqwOYt66fit2ffwUH5iVuTfxk4TY7N5ZWTq3CgonlyErz4T/vn0CKV7+NHzl1EjrGFKK/qdTkESJXkpOGbx3qQ4pP6D6jRMOpMj+D2cuU1IRd4wqKPiHEW3l5eXlvvfVWvDeFiIhOArVHHgMA3HjGlIhrjRIR0cnln//3Pn76+7+jrbog4iyvD05I7Lz7+yjMTMVVpw2VnHvvgxOWdZz/9Z8PkBGDBn8ni+BxwJjiLHzjvN74bgwRESWt/Px8vP32229LKfON13F6joiIaIS7Y/M0/Pz/vYPFkyrivSlERJRkstJ8aK8ttL+hA16PwKc3tIdcbtckkMHl6DhtalW8N4GIiEYoZjDHATOYiYiIiIiIaDi88ed/4vu//huWtY6yDeYTERGZYQYzERERERER0UmotjgLtcVZ8d4MIiIawTh9SURERERERERERESuMMBMRERERERERERERK4wwExERERERERERERErjDATERERERERERERESuMMBMRERERERERERERK4wwExERERERERERERErjDATERERERERERERESuMMBMRERERERERERERK4IKWW8t+GkI4Q4AUDk5eXFe1OIiIiIiIiIiIiILL399tsAIKWUIQnLDDDHgRAi+Ka/HdcNGZId+PnOSb4NWom0PdwWtUTaFiCxtofbYi5RtidRtiMoOOPJcSkxnt8oUbYnUbYjKJG2h9tiLpG2J5G2BUic7UmU7QjimJRYz2+UKNuTKNsRlCjbkyjbEcTtMcdtUUukbQESa0xKhPcmDwCklMJ4hW/4t4UQ+GBKKfPjvB0AACHEswAgpew9mbdBK5G2h9uilkjbAiTW9nBbzCXK9iTKdgQJId4COC4lyvMbJcr2JMp2BCXS9nBbzCXS9iTStgCJsz2Jsh1BHJMS6/mNEmV7EmU7ghJlexJlO4K4Pea4LWqJtC1AYo1JifDeBN8PFdZgJiIiIiIiIiIiIiJXGGAmIiIiIiIiIiIiIlcYYCYiIiIiIiIiIiIiVxhgJiIiIiIiIiIiIiJXhJQy3ttw0kmkIuFEREQcl4iIKFFwTCIiokTBMUnP6v1gBjMRERERERERERERucIAMxERERERERERERG5whIZREREREREREREROQKM5iJaEQRQvQKIaQQojfe20JERCc3jklERJQoOCYRUSwxwExECUkIsSlwANQa720hIqKTG8ckIiJKFByTiCgRMcBMRERERERERERERK4wwExERERERERERERErjDAHEVcqkIUO0KIN4QQdyguf1YI8ezwbxFRYuOYRBQ7HJOIwsMxiSh2OCYRhYdjUmwwwExERERERERERERErjDATERERERERERERESuMMAcQ0KIWUKI+4UQvxFC/J8Q4rdCiI8JITIMt7tDCPGWEGK0EOJLQoh3hBB/EkJcI4Twxmv7iYho5OCYREREiYJjEhERJQqOSdHhi/cGjHCrAGQC+BSAvwDoAHA2gKrAdVopAL4O4AUA5wGYC+AggF8E7k9ERBQJjklERJQoOCYREVGi4JgUBQwwx9ZhKeW/NL/fKoT4HwAfFkJUSyl/o7kuE8BdUsqPBH6/WQjxCoCtOMk/pEQB0uRyL4APhnNDiJIUxySi6OGYRBQZjklE0cMxiSgyHJOigCUyYkj7ARVCZAkhigG8CEAAmKK4yy2G358DUBe7LSRKKn8DkK+4vGaYt4MoKXFMIooqjklEEeCYRBRVHJOIIsAxKToYYI4hIUR1oEbLXwG8A+BPAL4ZuDrPcPN3pJR/NVz2NwAFMd5MomTxCwDThRCpwQuEEEsAjI7fJhElD45JRFHFMYkoAhyTiKKKYxJRBDgmRQdLZMRIoMD3kwAKAVwF4HUA/wRQCeAOhAb3uXSFyNptAE4D8IQQ4j4A9QDWwX9ARUQWOCYRRR3HJCKXOCYRRR3HJCKXOCZFDwPMsTMJwFgAG6WUdwUvFELMjd8mESUVEfj5AQBIKb8mhDgI4ACAjwN4GcASANfGZeuIkgvHJKLIcEwiih6OSUSR4ZhEFD0ck6KEAebYCc5qBHf+EEIIAOfEZ3OIkk5O4OffgxdIKa8DcJ3hdr3aX6SUz0LzvSMiAByTiCLFMYkoejgmEUWGYxJR9HBMihIGmGPndfiXpFwjhKiEf+e/EqzLQuTUNAD/APDbeG8I0QjAMYkoMhyTiKKHYxJRZDgmEUUPx6QoYZO/6BpcqiKlfA/AUgCvAjgK4BiAnwPYEJ9NI0oOQoiVQogbAawFcLeU8kS8t4koSXFMIooQxySiqOGYRBQhjklEUcMxKQaElDLe2zBiCCH2AbgeQK2U8tfx3h6iZCSE+BX8y74eBHCulPLdOG8SUVLimEQUOY5JRNHBMYkochyTiKKDY1JssERGdHGpClGEpJRj4r0NRCMExySiCHFMIooajklEEeKYRBQ1HJNigAHmKBBCrIS/gP5aADdzqQoREcULxyQiIkoUHJOIiChRcEyKLZbIiAIuVSEiokTBMYmIiBIFxyQiIkoUHJNiiwFmIiIiIiIiIiIiInLFE+8NICIiIiIiIiIiIqLkxAAzEREREREREREREbnCADMRERERERERERERucIAs0NCiGlCiJuEEP8lhPinEOI3Qoh7hRANitt2CyGeF0K8K4T4gxDieiFEpuE2FUKIK4UQ3xBC/EMIIYUQvYrHKhJCHBJCPCeE+JMQ4i0hxLeFEKti92qJiCjRxXFcEkKIW4QQPwyMSe8IIV4TQuwTQqTE7hUTEVGiiteYpHjsmsDjSiFEa9ReIBERJY14jklCiDcC1xv/XRmbV5s4fPHegCRyGMAMAPcD+CGAcgB7AfxACNEhpfwpAAQOZJ4G8BMABwBUATgPQB2ApZrHGxd4zP8JPF63yfN2AbgCwFcBfAjA+wBWArhPCHGJlPLy6L1EIiJKIvEalzwA2gB8HcCv4B+XugB8HEA7gA1Ren1ERJQ84jUmGV0D4ESEr4WIiJJbvMek78N/bqT1Y9evJkkIKWW8tyEpCCG6AbwspfyP5rJGAD8CcK+UclPgsq8CmAygSUr5TuCybQA+DWBASvlM4LIcAKlSyr8IIU4B8DCAPinls4bnHQPghJTy15rLBICn4D+hL5JS/ismL5qIiBJWvMYli+25Af4DtzIp5Z+i8iKJiCgpJMKYFMgm+xqAqwFcCGCKlPLVaL5OIiJKfPEck4QQbwB4VUp5SqxeX6JiiQyHpJQvaj+cgct+Dv9Mx3gAEELkApgL4K7ghzPgLgDvAFitue8/pJR/cfC8v9IGlwOXSQCPAMgAUOvm9RARUXKL17hk4dcABIC8CB6DiIiSULzHJCGEF8D1AD4Bf4YZERGdpOI9JgUeP81YamOkY4A5AoFM4jIAfw5cNAn+siMva28X+GC/CmBKFJ++PPDzz5a3IiKik8ZwjktCiBQhRLEQYrQQYgX8y8l+CX/ZDCIiOskN87nSDgCVAFg+kIiIQgzzmDQPwD8B/FMI8QshxFkRPFbSYIA5MmvhP5C5L/B7ReDn7xW3/T2AUdF4UiFEIYBtAJ7lMmQiItIYznFpPoA/AfgNgIcA/C+A5VLKDyJ4TCIiGjmGZUwKnBtdDuC4lPItN49BREQj3nCdJ/0QwDH4e6dthz+gfYsQ4ojLx0sabPLnkhCiCcBNAJ4H8LnAxRmBn/+nuMu/NddH8rweAJ+Hfwnyvkgfj4iIRoY4jEsvwb+sLA9AP4BWANkRPB4REY0QwzwmXQbgjwBudnl/IiIawYZzTJJSLjM89+2B571YCPEpKeXbbh43GTCD2QUhRDmAxwD8DcAqKWWwU3Gw2V6a4m7pmusjcSP8WWObpZQ/isLjERFRkovHuCSl/LOU8ikp5YNSyj0AHgXwZGBbiIjoJDWcY5IQYiKAnQAOSinfd7G5REQ0gsU5fofA6s6PA8gE0BWNx0xUDDCHSQiRB+Bx+DO25ksp/6C5OphaXxFyR/9lb0b43McA7AZwvpTyC5E8FhERjQzxHJcMHoA/g3l5FB+TiIiSSBzGpA8DeAXAfwkhaoUQtQCKA9eNEkKMdvGYREQ0AiTQedJvAz8Lo/iYCYcB5jAIIdIBfBnAWABLpJQ/M9zkxwDeB9BuuF8q/EuHX43gufcAOA7gY1LKa9w+DhERjRzxHJcUgsvI8qL4mERElCTiNCZVA5gGf4PZ4L+rA9c9BuB7Lh6TiIiSXIKdJ9UFfo7oHmoMMDskhPAC+CL8Ke2rpJQvGW8TqKXyFID1QghtHcr18Gd13e/yuU8HcAP8tZcPunkMIiIaWeI1LgkhCgPPbbQt8PP74T4mEREltzieK50LYIXh342B6w4A2OTiMYmIKInF+TzJY7gsHcAhAP8A8O1wHzOZsMmfc9cCWAb/DEihEGKd5rp3pJSPBP5/IYAXATwrhLgNQBX8QeHHpZRPaR9QCHFR4L/jAz/XCyFmAnhLSvmJwG06ANwF4C8AngawVgihfZgnpZT/LzovkYiIkkhcxqXAc14khHgIwC8AZAGYB39/gMeklE9H8TUSEVFyiMuYJKX8hnFDhBD5gf9+Q0r5aoSvi4iIkk88z5MuFEI8AOANAEUANsKfRb1LSvlO9F5i4hFSynhvQ1IQQjwLYLbJ1b+WUtZqbjsTwFUA2gD8Hf6Zk6NSyn8aHtPszR98PCHEJgC3W2xan5TyWdsXQEREI0ocx6WJAC6APyOgHMAJAD+Df5XNDVLK99y9IiIiSlbxGpNMtmUT/OdPUxhgJiI6+cTxPGkq/KVtpwAoAfB/8PcJuEZK+RV3ryZ5MMBMRERERERERERERK6wBjMRERERERERERERucIAMxERERERERERERG5wgAzEREREREREREREbnCADMRERERERERERERucIAMxERERERERERERG5wgAzEREREREREREREbnCADMRERERERERERERucIAMxERERFREhBC3CGEkPHeDiIiIiIiLV+8N4CIiIiI6GQUZrB4TMw2hIiIiIgoAkJKJkEQEREREQ03IcQ6w0WzAJwF4FYAzxmuexjAfwB4pZT/HobNIyIiIiJyhBnMRERERERxIKW8W/u7EMIHf4D528brNN6L+YYREREREYWBNZiJiIiIiJKAqgZz8DIhRFHg/38WQvxDCPGIEKI8cJuzhBA/FUL8WwjxuhBiucnjny6EeD5w/3eFEN8RQpw2HK+NiIiIiJIXA8xERERERMnvCQB5AC4B8GkASwA8LIQ4BOAQgDsBHAGQCuABIYSuprMQ4kMA7gXwDwAXB277LoD7hRB7hutFEBEREVHyYYkMIiIiIqLk910p5WAgWAgBAOcCqAQwUUr598DlzwB4Df5SHEcDl7UBuBDAR6SUF2ge8wYhxCMAPiKEuEtK+Y/heCFERERElFyYwUxERERElPw+bvg92CTwrmBwGQCklD8E8HcAjZrbrgUgAdwphCjW/gPwJQA5ALpituVERERElNSYwUxERERElPx+afj9b4Gfv1Lc9m8AijS/jwcgALxu8fhl7jeNiIiIiEYyBpiJiIiIiJKclPIDk6vMLheG/0sACy1u/xOXm0ZEREREIxwDzEREREREJ7efA1gA4DdSyp/Ge2OIiIiIKLmwBjMRERER0cntc4GfHxZCeI1XCiFYHoOIiIiITDGDmYiIiIjoJCal/J4Q4jiA4wBeFULcD+BNABUApgJYBCA1bhtIRERERAmNAWYiIiIiopOclPJSIcTLAPYB2A8gC8AfAfw4cBkRERERkZKQUsZ7G4iIiIiIiIiIiIgoCbEGMxERERERERERERG5wgAzEREREREREREREbnCADMRERERERERERERucIAMxERERERERERERG5wgAzEREREREREREREbnCADMRERERERERERERucIAMxERERERERERERG5wgAzEREREREREREREbnCADMRERERERERERERufL/AfsgxeheXZZaAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 1440x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=[20, 5])\n",
    "data.loc[\"2012\":].plot(y=\"demand\", legend=None, ax=ax)\n",
    "ax.set_xlabel(\"Time\")\n",
    "ax.set_ylabel(\"Electricity Demand\")\n",
    "ax.set_title(\"Electricity Demand\")\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d2683607-c1ab-4b60-b700-05ae7d36f105",
   "metadata": {},
   "source": [
    "# Creating Fourier features with sktime"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "2cf14b06-1206-4217-9ba2-559739d130b4",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sktime.transformations.series.fourier import FourierFeatures"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "38419a54-8300-4934-860a-a590b045dcbb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>sin_24_1</th>\n",
       "      <th>cos_24_1</th>\n",
       "      <th>sin_24_2</th>\n",
       "      <th>cos_24_2</th>\n",
       "      <th>sin_24_3</th>\n",
       "      <th>cos_24_3</th>\n",
       "      <th>sin_168_1</th>\n",
       "      <th>cos_168_1</th>\n",
       "      <th>sin_168_2</th>\n",
       "      <th>cos_168_2</th>\n",
       "      <th>sin_168_3</th>\n",
       "      <th>cos_168_3</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>date_time</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2002-01-01 00:00:00</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2002-01-01 01:00:00</th>\n",
       "      <td>0.258819</td>\n",
       "      <td>0.965926</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>8.660254e-01</td>\n",
       "      <td>7.071068e-01</td>\n",
       "      <td>7.071068e-01</td>\n",
       "      <td>0.037391</td>\n",
       "      <td>0.999301</td>\n",
       "      <td>0.074730</td>\n",
       "      <td>0.997204</td>\n",
       "      <td>0.111964</td>\n",
       "      <td>0.993712</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2002-01-01 02:00:00</th>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.866025</td>\n",
       "      <td>0.866025</td>\n",
       "      <td>5.000000e-01</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>6.123234e-17</td>\n",
       "      <td>0.074730</td>\n",
       "      <td>0.997204</td>\n",
       "      <td>0.149042</td>\n",
       "      <td>0.988831</td>\n",
       "      <td>0.222521</td>\n",
       "      <td>0.974928</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2002-01-01 03:00:00</th>\n",
       "      <td>0.707107</td>\n",
       "      <td>0.707107</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>6.123234e-17</td>\n",
       "      <td>7.071068e-01</td>\n",
       "      <td>-7.071068e-01</td>\n",
       "      <td>0.111964</td>\n",
       "      <td>0.993712</td>\n",
       "      <td>0.222521</td>\n",
       "      <td>0.974928</td>\n",
       "      <td>0.330279</td>\n",
       "      <td>0.943883</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2002-01-01 04:00:00</th>\n",
       "      <td>0.866025</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.866025</td>\n",
       "      <td>-5.000000e-01</td>\n",
       "      <td>1.224647e-16</td>\n",
       "      <td>-1.000000e+00</td>\n",
       "      <td>0.149042</td>\n",
       "      <td>0.988831</td>\n",
       "      <td>0.294755</td>\n",
       "      <td>0.955573</td>\n",
       "      <td>0.433884</td>\n",
       "      <td>0.900969</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     sin_24_1  cos_24_1  sin_24_2      cos_24_2      sin_24_3  \\\n",
       "date_time                                                                       \n",
       "2002-01-01 00:00:00  0.000000  1.000000  0.000000  1.000000e+00  0.000000e+00   \n",
       "2002-01-01 01:00:00  0.258819  0.965926  0.500000  8.660254e-01  7.071068e-01   \n",
       "2002-01-01 02:00:00  0.500000  0.866025  0.866025  5.000000e-01  1.000000e+00   \n",
       "2002-01-01 03:00:00  0.707107  0.707107  1.000000  6.123234e-17  7.071068e-01   \n",
       "2002-01-01 04:00:00  0.866025  0.500000  0.866025 -5.000000e-01  1.224647e-16   \n",
       "\n",
       "                         cos_24_3  sin_168_1  cos_168_1  sin_168_2  cos_168_2  \\\n",
       "date_time                                                                       \n",
       "2002-01-01 00:00:00  1.000000e+00   0.000000   1.000000   0.000000   1.000000   \n",
       "2002-01-01 01:00:00  7.071068e-01   0.037391   0.999301   0.074730   0.997204   \n",
       "2002-01-01 02:00:00  6.123234e-17   0.074730   0.997204   0.149042   0.988831   \n",
       "2002-01-01 03:00:00 -7.071068e-01   0.111964   0.993712   0.222521   0.974928   \n",
       "2002-01-01 04:00:00 -1.000000e+00   0.149042   0.988831   0.294755   0.955573   \n",
       "\n",
       "                     sin_168_3  cos_168_3  \n",
       "date_time                                  \n",
       "2002-01-01 00:00:00   0.000000   1.000000  \n",
       "2002-01-01 01:00:00   0.111964   0.993712  \n",
       "2002-01-01 02:00:00   0.222521   0.974928  \n",
       "2002-01-01 03:00:00   0.330279   0.943883  \n",
       "2002-01-01 04:00:00   0.433884   0.900969  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "transformer = FourierFeatures(\n",
    "    sp_list=[24, 24 * 7],  # list of seasonal periods\n",
    "    fourier_terms_list=[3, 3],  # list of fourier terms\n",
    "    freq=\"H\",  # Frequency of the time series\n",
    "    keep_original_columns=False,\n",
    ")\n",
    "\n",
    "transformer.fit(data)\n",
    "result = transformer.transform(data)\n",
    "result.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "21b0f35a-8e03-4fd1-aff2-8141be2bb5de",
   "metadata": {},
   "source": [
    "Let's visualise the features that we're using to capture seasonality."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "3b7151c6-f45f-47c3-85ac-ac3a56442221",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x720 with 6 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Let's filter to the weekly seasonality Fourier features\n",
    "seasonal_period = 24 * 7\n",
    "result_ = result.filter(like=f\"_{seasonal_period}_\").iloc[-seasonal_period * 3 :]\n",
    "\n",
    "# Plot each Fourier feature associated to the specified seasonality\n",
    "num_features = result_.shape[1]\n",
    "fig, ax = plt.subplots(nrows=num_features // 2, ncols=2, figsize=(12, 10), sharex=True)\n",
    "for feature, ax in zip(result_.columns, ax.flatten()):\n",
    "    result_.loc[:, feature].plot(ax=ax)\n",
    "    ax.set_title(feature)\n",
    "\n",
    "fig.suptitle(f\"Fourier features for seasonal period: {seasonal_period}\", fontsize=18)\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a59a8e58-1138-4e59-9a47-e3bdee6a271a",
   "metadata": {},
   "source": [
    "We have sine and cosine waves with frequencies which are integer multiples of `seasonal_period`. The number of features is equivalent to the number of `fourier_terms * 2`, the factor of 2 comes from the fact the we have both a sine and cosine wave associated with each frequency."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7fe0abdd-79dd-42db-aaea-7449f39eb7f7",
   "metadata": {},
   "source": [
    "# Let's see how fourier features help capture seasonality."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7107d5aa-2e67-47df-9b67-edf670d5b022",
   "metadata": {},
   "source": [
    "Let's build a linear model using only fourier features to understand how they help capture seasonality.\n",
    "\n",
    "In a linear model we have: $$y_t = \\beta_0 + \\beta_1x_1 + ... + \\beta_Nx_N$$\n",
    "\n",
    "where $N$ is the number of features.\n",
    "\n",
    "For this dataset we want to model daily and weekly seasonality alongside other features, $x_i$. Effectively we want to fit a model that looks like the following:\n",
    "\n",
    "$$y_t = \\beta_0 + \\beta_1x_1 + \\beta_2x_2 + ... + S^{daily}_t + S^{weekly}_t$$\n",
    "\n",
    "where $S^{daily}_t$ and $S^{weekly}_t$ represent the daily and weekly seasonal component. As discussed in lectures, when using fourier features we are modelling each of these seasonal components using a sum of sine and cosine functions which have frequencies that are integer multiples of the seasonal period:\n",
    "\n",
    "$$\n",
    "S^{daily}_t = \\sum_{n=1}^{n_{daily}} A_{n}^{daily}sin(\\frac{2\\pi nt}{24}) + B_{n}^{daily}cos(\\frac{2\\pi nt }{24})\n",
    "$$\n",
    "$$\n",
    "S^{weekly}_t = \\sum_{n=1}^{n_{weekly}} A_{n}^{weekly}sin(\\frac{2\\pi nt}{24*7}) + B_{n}^{weekly}cos(\\frac{2\\pi nt }{24*7})\n",
    "$$\n",
    "\n",
    "where $A_{n}$ and $B_{n}$ are the coefficients (i.e., they're just additional $\\beta$ coefficients corresponding to the sine and cosine features in the linear model) learned when we train the linear model, $n_{daily}$ & $n_{weekly}$ are hyperparameters which represents the number of sine and cosine features we want to use to model the respective seasonal component.\n",
    "\n",
    "If we are only using fourier features, the linear model that we're effectively fitting is: \n",
    "$$\n",
    "\\begin{aligned}\n",
    "y_t &= \\sum_{p}\\sum_{n=1}^{n_p} A_{n,p}sin(\\frac{2\\pi nt}{T_p}) + B_{n,p}cos(\\frac{2\\pi nt }{T_p}) \\\\\n",
    "&= \\sum_{n=1}^{n_{daily}} A_{n}^{daily}sin(\\frac{2\\pi nt}{24}) + B_{n}^{daily}cos(\\frac{2\\pi nt }{24}) +  \\sum_{n=1}^{n_{weekly}} A_{n}^{weekly}sin(\\frac{2\\pi nt}{24*7}) + B_{n}^{weekly}cos(\\frac{2\\pi nt }{24*7})\n",
    "\\end{aligned}\n",
    "$$\n",
    "\n",
    "where $p$ represents the seasonality we are modelling."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "7f1ef5ea-76f1-416e-a354-2fc4c08e6b4b",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.linear_model import LinearRegression"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "456830dc-4700-41cb-8d60-bf5b522c74a2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>demand</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>date_time</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2002-01-01 00:00:00</th>\n",
       "      <td>6919.366092</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2002-01-01 01:00:00</th>\n",
       "      <td>7165.974188</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2002-01-01 02:00:00</th>\n",
       "      <td>6406.542994</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2002-01-01 03:00:00</th>\n",
       "      <td>5815.537828</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2002-01-01 04:00:00</th>\n",
       "      <td>5497.732922</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                          demand\n",
       "date_time                       \n",
       "2002-01-01 00:00:00  6919.366092\n",
       "2002-01-01 01:00:00  7165.974188\n",
       "2002-01-01 02:00:00  6406.542994\n",
       "2002-01-01 03:00:00  5815.537828\n",
       "2002-01-01 04:00:00  5497.732922"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = data.copy()\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "5de1699c-0610-4876-a50f-9d1591113ec1",
   "metadata": {},
   "outputs": [],
   "source": [
    "fourier_feats = FourierFeatures(\n",
    "    # List of seasonal periods\n",
    "    sp_list=[\n",
    "        24,  # daily seasonality\n",
    "        24 * 7,  # weekly seasonality\n",
    "        24 * 365,  # yearly seasonality\n",
    "    ],\n",
    "    # The number of fourier components for each seasonality.\n",
    "    fourier_terms_list=[\n",
    "        3,  # daily seasonality\n",
    "        3,  # weekly seasonality\n",
    "        3,  # yearly seasonality\n",
    "    ],\n",
    "    freq=\"H\",  # Frequency of time series\n",
    "    keep_original_columns=False,\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "41f2c79c-20fd-4cba-b6b6-221092d976ea",
   "metadata": {},
   "source": [
    "Split data into train and test."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "f0965925-e716-429f-8fe7-c97bec7ff135",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Hold out the last 2 weeks of obeservations\n",
    "holdout_size = 24 * 7 * 2\n",
    "df_train = data.iloc[:-holdout_size]\n",
    "df_test = data.iloc[-holdout_size:]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "627becc6-3cba-40ef-8ce0-2ae7119078e7",
   "metadata": {},
   "source": [
    "Creat fourier features."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "ccb28c56-7136-497a-9b16-f29dee0edb75",
   "metadata": {},
   "outputs": [],
   "source": [
    "target = [\"demand\"]\n",
    "\n",
    "X_train = fourier_feats.fit_transform(df_train)\n",
    "y_train = df_train.loc[:, target]\n",
    "\n",
    "X_test = fourier_feats.transform(df_test)\n",
    "y_test = df_test.loc[:, target]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "49d45549-ec47-486c-9a2a-019c0c1af225",
   "metadata": {},
   "source": [
    "We have the fourier features for both the training and testing period. So we can use these to directly predict the entire test period without having to use direct or recursive forecasting. We show later in this notebook how to use fourier features alongside other features which requires us to use a direct or recursive forecasting workflow to do multistep forecasting."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "34860111-3393-444d-a8a6-1929773bcf4d",
   "metadata": {},
   "outputs": [],
   "source": [
    "model = LinearRegression()\n",
    "model.fit(X_train, y_train)\n",
    "\n",
    "y_forecast_train = model.predict(X_train)\n",
    "y_forecast_train = pd.DataFrame(y_forecast_train, index=X_train.index, columns=target)\n",
    "\n",
    "y_forecast_test = model.predict(X_test)\n",
    "y_forecast_test = pd.DataFrame(y_forecast_test, index=X_test.index, columns=target)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "dabbc2cc-3d3d-4f3b-9433-e841436cc0fb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Forecast with LinearRegression()')"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# --- PLOTTING --- #\n",
    "# Plot the forecast.\n",
    "fig, ax = plt.subplots(figsize=[15, 7])\n",
    "\n",
    "# Plot training set.\n",
    "y_train.plot(ax=ax, marker=\".\", alpha=0.5)\n",
    "# Plot actuals in forecasting horizon.\n",
    "y_test.plot(ax=ax, marker=\".\", alpha=0.5)\n",
    "# Plot forecast in testing data.\n",
    "y_forecast_test.plot(ax=ax)\n",
    "# Plot forecasts in training data.\n",
    "y_forecast_train.plot(ax=ax)\n",
    "\n",
    "ax.legend([\"train\", \"test\", \"forecast\", \"in-sample forecast\"])\n",
    "ax.set_xlim(xmin=y_train.index.max() - pd.DateOffset(weeks=2))\n",
    "ax.set_xlabel(\"Time\")\n",
    "ax.set_ylabel(f\"{target}\")\n",
    "ax.set_title(f\"Forecast with {model}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2981667e-663a-4582-97c3-940c326938bb",
   "metadata": {},
   "source": [
    "We can see that just using Fourier features we are able to capture daily and weekly seasonality. In the absence of other features the forecast is completely periodic; this is expected because the model is just a sum of sine and cosine functions.\n",
    "\n",
    "Try adjusting the number of Fourier terms in the `fourier_terms_list` argument and see how it changes the predictions.\n",
    "\n",
    "Let's add more features alongside Fourier features and build a forecast!"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9d20fba2-1d7b-472c-a73a-d67e55173bb7",
   "metadata": {},
   "source": [
    "# Let's build some forecasts!"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5e835157-d0e9-4571-81dc-6fa818ffb032",
   "metadata": {},
   "source": [
    "Let's build a recursive forecast and see how we can include Fourier features in our feature engineering pipeline."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "738606c1-df44-4f9f-b4d7-4e5a1f22d234",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Fourier features\n",
    "from sktime.transformations.series.fourier import FourierFeatures\n",
    "\n",
    "# --- The transformers from earlier in the course. --- #\n",
    "# Date time features to capture seasonality\n",
    "from sktime.transformations.series.date import DateTimeFeatures\n",
    "# Require OneHotEncoder to create seasonal dummy variables\n",
    "from sklearn.preprocessing import OneHotEncoder\n",
    "# Lag and window features\n",
    "from sktime.transformations.series.summarize import WindowSummarizer\n",
    "# Time features for trend \n",
    "from sktime.transformations.series.time_since import TimeSince\n",
    "from sklearn.preprocessing import PolynomialFeatures\n",
    "# Rescaling transformer for linear models with regularisation\n",
    "from sklearn.preprocessing import MinMaxScaler\n",
    "# Pipelines to create feature engineering pipeline\n",
    "from sklearn.pipeline import make_pipeline, make_union\n",
    "# Used to reset sklearn estimators\n",
    "from sklearn.base import clone\n",
    "\n",
    "# Let's ensure all sklearn transformers output pandas dataframes\n",
    "from sklearn import set_config\n",
    "set_config(transform_output=\"pandas\")  # Upgrade to scikit-learn 0.12\n",
    "                                       # for this feature"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "130d5c18-2870-4a1a-89af-c09bdff6b775",
   "metadata": {},
   "outputs": [
    {
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>demand</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>date_time</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2002-01-01 00:00:00</th>\n",
       "      <td>6919.366092</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2002-01-01 01:00:00</th>\n",
       "      <td>7165.974188</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2002-01-01 02:00:00</th>\n",
       "      <td>6406.542994</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2002-01-01 03:00:00</th>\n",
       "      <td>5815.537828</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2002-01-01 04:00:00</th>\n",
       "      <td>5497.732922</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                          demand\n",
       "date_time                       \n",
       "2002-01-01 00:00:00  6919.366092\n",
       "2002-01-01 01:00:00  7165.974188\n",
       "2002-01-01 02:00:00  6406.542994\n",
       "2002-01-01 03:00:00  5815.537828\n",
       "2002-01-01 04:00:00  5497.732922"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = data.copy()\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7d292e0e-e5ce-4c5d-b63a-6490a6457b6b",
   "metadata": {},
   "source": [
    "Specify target name."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "25d2262f-c242-409b-93b4-0913f70c3113",
   "metadata": {},
   "outputs": [],
   "source": [
    "target = [\"demand\"]  # Note: it's in a list.\n",
    "                    # This ensures we'll get\n",
    "                    # a dataframe when using df.loc[:, target]\n",
    "                    # rather than a pandas Series.\n",
    "                    # This can also be useful if we have\n",
    "                    # multiple targets."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3dac1165-9d17-4648-b7ed-927ed660de3d",
   "metadata": {},
   "source": [
    "Prepare our transformers."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "002c3527-412a-4dc4-b359-1c829a8a4789",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Polynomial time features for trend\n",
    "time_feats = make_pipeline(\n",
    "    TimeSince(), PolynomialFeatures(degree=1, include_bias=False)\n",
    ")\n",
    "\n",
    "# Datetime features\n",
    "# Specify which datetime features to create\n",
    "datetime_features = [\n",
    "    \"is_weekend\",\n",
    "]\n",
    "\n",
    "datetime_feats = DateTimeFeatures(\n",
    "    manual_selection=datetime_features,\n",
    "    keep_original_columns=False,\n",
    ")\n",
    "\n",
    "# Create the fourier features\n",
    "fourier_feats = FourierFeatures(\n",
    "    sp_list=[24, 24 * 7],\n",
    "    fourier_terms_list=[3, 3],\n",
    "    freq=\"H\",\n",
    "    keep_original_columns=False,\n",
    ")\n",
    "\n",
    "\n",
    "# Features computed from the target.\n",
    "# Compute lag and window features.\n",
    "lag_window_feats = WindowSummarizer(\n",
    "    lag_feature={\n",
    "        \"lag\": [1,2,3,4] # np.arange(1, 25),  # Lag features.\n",
    "#        \"mean\": [[1, 24], [1, 24 * 7]],  # [[lag, window size]]\n",
    "    },\n",
    "    target_cols=target,\n",
    "    truncate=\"bfill\",  # Backfill missing values from lagging and windowing.\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1d0525e4-b9a3-4977-88e6-cc213e4d8a9e",
   "metadata": {},
   "source": [
    "Create a pipeline to create all our features."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "8224a415-81da-4471-9e65-53f0ed4b7ed4",
   "metadata": {},
   "outputs": [],
   "source": [
    "pipeline = make_union(\n",
    "    datetime_feats,\n",
    "    fourier_feats,\n",
    "    time_feats,\n",
    "    lag_window_feats,\n",
    ")\n",
    "\n",
    "# Apply min-max scaling to all the features\n",
    "pipeline = make_pipeline(pipeline, MinMaxScaler())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "b74e1d09-c547-42dc-b736-f3e55d756749",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>#sk-container-id-1 {color: black;background-color: white;}#sk-container-id-1 pre{padding: 0;}#sk-container-id-1 div.sk-toggleable {background-color: white;}#sk-container-id-1 label.sk-toggleable__label {cursor: pointer;display: block;width: 100%;margin-bottom: 0;padding: 0.3em;box-sizing: border-box;text-align: center;}#sk-container-id-1 label.sk-toggleable__label-arrow:before {content: \"▸\";float: left;margin-right: 0.25em;color: #696969;}#sk-container-id-1 label.sk-toggleable__label-arrow:hover:before {color: black;}#sk-container-id-1 div.sk-estimator:hover label.sk-toggleable__label-arrow:before {color: black;}#sk-container-id-1 div.sk-toggleable__content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;background-color: #f0f8ff;}#sk-container-id-1 div.sk-toggleable__content pre {margin: 0.2em;color: black;border-radius: 0.25em;background-color: #f0f8ff;}#sk-container-id-1 input.sk-toggleable__control:checked~div.sk-toggleable__content {max-height: 200px;max-width: 100%;overflow: auto;}#sk-container-id-1 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {content: \"▾\";}#sk-container-id-1 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-1 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-1 input.sk-hidden--visually {border: 0;clip: rect(1px 1px 1px 1px);clip: rect(1px, 1px, 1px, 1px);height: 1px;margin: -1px;overflow: hidden;padding: 0;position: absolute;width: 1px;}#sk-container-id-1 div.sk-estimator {font-family: monospace;background-color: #f0f8ff;border: 1px dotted black;border-radius: 0.25em;box-sizing: border-box;margin-bottom: 0.5em;}#sk-container-id-1 div.sk-estimator:hover {background-color: #d4ebff;}#sk-container-id-1 div.sk-parallel-item::after {content: \"\";width: 100%;border-bottom: 1px solid gray;flex-grow: 1;}#sk-container-id-1 div.sk-label:hover label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-1 div.sk-serial::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: 0;}#sk-container-id-1 div.sk-serial {display: flex;flex-direction: column;align-items: center;background-color: white;padding-right: 0.2em;padding-left: 0.2em;position: relative;}#sk-container-id-1 div.sk-item {position: relative;z-index: 1;}#sk-container-id-1 div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: white;position: relative;}#sk-container-id-1 div.sk-item::before, #sk-container-id-1 div.sk-parallel-item::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: -1;}#sk-container-id-1 div.sk-parallel-item {display: flex;flex-direction: column;z-index: 1;position: relative;background-color: white;}#sk-container-id-1 div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;}#sk-container-id-1 div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;}#sk-container-id-1 div.sk-parallel-item:only-child::after {width: 0;}#sk-container-id-1 div.sk-dashed-wrapped {border: 1px dashed gray;margin: 0 0.4em 0.5em 0.4em;box-sizing: border-box;padding-bottom: 0.4em;background-color: white;}#sk-container-id-1 div.sk-label label {font-family: monospace;font-weight: bold;display: inline-block;line-height: 1.2em;}#sk-container-id-1 div.sk-label-container {text-align: center;}#sk-container-id-1 div.sk-container {/* jupyter's `normalize.less` sets `[hidden] { display: none; }` but bootstrap.min.css set `[hidden] { display: none !important; }` so we also need the `!important` here to be able to override the default hidden behavior on the sphinx rendered scikit-learn.org. See: https://github.com/scikit-learn/scikit-learn/issues/21755 */display: inline-block !important;position: relative;}#sk-container-id-1 div.sk-text-repr-fallback {display: none;}</style><div id=\"sk-container-id-1\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>Pipeline(steps=[(&#x27;featureunion&#x27;,\n",
       "                 FeatureUnion(transformer_list=[(&#x27;datetimefeatures&#x27;,\n",
       "                                                 DateTimeFeatures(manual_selection=[&#x27;is_weekend&#x27;])),\n",
       "                                                (&#x27;fourierfeatures&#x27;,\n",
       "                                                 FourierFeatures(fourier_terms_list=[3,\n",
       "                                                                                     3],\n",
       "                                                                 freq=&#x27;H&#x27;,\n",
       "                                                                 sp_list=[24,\n",
       "                                                                          168])),\n",
       "                                                (&#x27;pipeline&#x27;,\n",
       "                                                 Pipeline(steps=[(&#x27;timesince&#x27;,\n",
       "                                                                  TimeSince()),\n",
       "                                                                 (&#x27;polynomialfeatures&#x27;,\n",
       "                                                                  PolynomialFeatures(degree=1,\n",
       "                                                                                     include_bias=False))])),\n",
       "                                                (&#x27;windowsummarizer&#x27;,\n",
       "                                                 WindowSummarizer(lag_feature={&#x27;lag&#x27;: [1,\n",
       "                                                                                       2,\n",
       "                                                                                       3,\n",
       "                                                                                       4]},\n",
       "                                                                  target_cols=[&#x27;demand&#x27;],\n",
       "                                                                  truncate=&#x27;bfill&#x27;))])),\n",
       "                (&#x27;minmaxscaler&#x27;, MinMaxScaler())])</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item sk-dashed-wrapped\"><div class=\"sk-label-container\"><div class=\"sk-label sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-1\" type=\"checkbox\" ><label for=\"sk-estimator-id-1\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">Pipeline</label><div class=\"sk-toggleable__content\"><pre>Pipeline(steps=[(&#x27;featureunion&#x27;,\n",
       "                 FeatureUnion(transformer_list=[(&#x27;datetimefeatures&#x27;,\n",
       "                                                 DateTimeFeatures(manual_selection=[&#x27;is_weekend&#x27;])),\n",
       "                                                (&#x27;fourierfeatures&#x27;,\n",
       "                                                 FourierFeatures(fourier_terms_list=[3,\n",
       "                                                                                     3],\n",
       "                                                                 freq=&#x27;H&#x27;,\n",
       "                                                                 sp_list=[24,\n",
       "                                                                          168])),\n",
       "                                                (&#x27;pipeline&#x27;,\n",
       "                                                 Pipeline(steps=[(&#x27;timesince&#x27;,\n",
       "                                                                  TimeSince()),\n",
       "                                                                 (&#x27;polynomialfeatures&#x27;,\n",
       "                                                                  PolynomialFeatures(degree=1,\n",
       "                                                                                     include_bias=False))])),\n",
       "                                                (&#x27;windowsummarizer&#x27;,\n",
       "                                                 WindowSummarizer(lag_feature={&#x27;lag&#x27;: [1,\n",
       "                                                                                       2,\n",
       "                                                                                       3,\n",
       "                                                                                       4]},\n",
       "                                                                  target_cols=[&#x27;demand&#x27;],\n",
       "                                                                  truncate=&#x27;bfill&#x27;))])),\n",
       "                (&#x27;minmaxscaler&#x27;, MinMaxScaler())])</pre></div></div></div><div class=\"sk-serial\"><div class=\"sk-item sk-dashed-wrapped\"><div class=\"sk-label-container\"><div class=\"sk-label sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-2\" type=\"checkbox\" ><label for=\"sk-estimator-id-2\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">featureunion: FeatureUnion</label><div class=\"sk-toggleable__content\"><pre>FeatureUnion(transformer_list=[(&#x27;datetimefeatures&#x27;,\n",
       "                                DateTimeFeatures(manual_selection=[&#x27;is_weekend&#x27;])),\n",
       "                               (&#x27;fourierfeatures&#x27;,\n",
       "                                FourierFeatures(fourier_terms_list=[3, 3],\n",
       "                                                freq=&#x27;H&#x27;, sp_list=[24, 168])),\n",
       "                               (&#x27;pipeline&#x27;,\n",
       "                                Pipeline(steps=[(&#x27;timesince&#x27;, TimeSince()),\n",
       "                                                (&#x27;polynomialfeatures&#x27;,\n",
       "                                                 PolynomialFeatures(degree=1,\n",
       "                                                                    include_bias=False))])),\n",
       "                               (&#x27;windowsummarizer&#x27;,\n",
       "                                WindowSummarizer(lag_feature={&#x27;lag&#x27;: [1, 2, 3,\n",
       "                                                                      4]},\n",
       "                                                 target_cols=[&#x27;demand&#x27;],\n",
       "                                                 truncate=&#x27;bfill&#x27;))])</pre></div></div></div><div class=\"sk-parallel\"><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class=\"sk-label-container\"><div class=\"sk-label sk-toggleable\"><label>datetimefeatures</label></div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-3\" type=\"checkbox\" ><label for=\"sk-estimator-id-3\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">DateTimeFeatures</label><div class=\"sk-toggleable__content\"><pre>DateTimeFeatures(manual_selection=[&#x27;is_weekend&#x27;])</pre></div></div></div></div></div></div><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class=\"sk-label-container\"><div class=\"sk-label sk-toggleable\"><label>fourierfeatures</label></div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-4\" type=\"checkbox\" ><label for=\"sk-estimator-id-4\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">FourierFeatures</label><div class=\"sk-toggleable__content\"><pre>FourierFeatures(fourier_terms_list=[3, 3], freq=&#x27;H&#x27;, sp_list=[24, 168])</pre></div></div></div></div></div></div><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class=\"sk-label-container\"><div class=\"sk-label sk-toggleable\"><label>pipeline</label></div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-5\" type=\"checkbox\" ><label for=\"sk-estimator-id-5\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">TimeSince</label><div class=\"sk-toggleable__content\"><pre>TimeSince()</pre></div></div></div><div class=\"sk-item\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-6\" type=\"checkbox\" ><label for=\"sk-estimator-id-6\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">PolynomialFeatures</label><div class=\"sk-toggleable__content\"><pre>PolynomialFeatures(degree=1, include_bias=False)</pre></div></div></div></div></div></div></div></div><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class=\"sk-label-container\"><div class=\"sk-label sk-toggleable\"><label>windowsummarizer</label></div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-7\" type=\"checkbox\" ><label for=\"sk-estimator-id-7\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">WindowSummarizer</label><div class=\"sk-toggleable__content\"><pre>WindowSummarizer(lag_feature={&#x27;lag&#x27;: [1, 2, 3, 4]}, target_cols=[&#x27;demand&#x27;],\n",
       "                 truncate=&#x27;bfill&#x27;)</pre></div></div></div></div></div></div></div></div><div class=\"sk-item\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-8\" type=\"checkbox\" ><label for=\"sk-estimator-id-8\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">MinMaxScaler</label><div class=\"sk-toggleable__content\"><pre>MinMaxScaler()</pre></div></div></div></div></div></div></div>"
      ],
      "text/plain": [
       "Pipeline(steps=[('featureunion',\n",
       "                 FeatureUnion(transformer_list=[('datetimefeatures',\n",
       "                                                 DateTimeFeatures(manual_selection=['is_weekend'])),\n",
       "                                                ('fourierfeatures',\n",
       "                                                 FourierFeatures(fourier_terms_list=[3,\n",
       "                                                                                     3],\n",
       "                                                                 freq='H',\n",
       "                                                                 sp_list=[24,\n",
       "                                                                          168])),\n",
       "                                                ('pipeline',\n",
       "                                                 Pipeline(steps=[('timesince',\n",
       "                                                                  TimeSince()),\n",
       "                                                                 ('polynomialfeatures',\n",
       "                                                                  PolynomialFeatures(degree=1,\n",
       "                                                                                     include_bias=False))])),\n",
       "                                                ('windowsummarizer',\n",
       "                                                 WindowSummarizer(lag_feature={'lag': [1,\n",
       "                                                                                       2,\n",
       "                                                                                       3,\n",
       "                                                                                       4]},\n",
       "                                                                  target_cols=['demand'],\n",
       "                                                                  truncate='bfill'))])),\n",
       "                ('minmaxscaler', MinMaxScaler())])"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pipeline"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6decf02c-1a0a-45d0-9fec-07255f232a17",
   "metadata": {},
   "source": [
    "Let's check how our feature engineering pipeline behaves."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "8071a5af-cfb4-4a2b-85d8-d0e065f53fa3",
   "metadata": {},
   "outputs": [
    {
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       "      <th></th>\n",
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       "      <th>demand_lag_3</th>\n",
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       "      <td>0.0</td>\n",
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       "      <td>0.937391</td>\n",
       "      <td>0.253533</td>\n",
       "      <td>0.937061</td>\n",
       "      <td>0.258052</td>\n",
       "      <td>0.936507</td>\n",
       "      <td>0.25</td>\n",
       "      <td>0.817386</td>\n",
       "      <td>0.675273</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2002-01-01 02:00:00</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.577350</td>\n",
       "      <td>0.732051</td>\n",
       "      <td>0.866025</td>\n",
       "      <td>0.666667</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.501402</td>\n",
       "      <td>0.749650</td>\n",
       "      <td>0.505648</td>\n",
       "      <td>0.748596</td>\n",
       "      <td>0.512858</td>\n",
       "      <td>0.746826</td>\n",
       "      <td>0.50</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.675273</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2002-01-01 03:00:00</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.816497</td>\n",
       "      <td>0.414214</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.333333</td>\n",
       "      <td>7.071068e-01</td>\n",
       "      <td>0.146447</td>\n",
       "      <td>0.751226</td>\n",
       "      <td>0.437041</td>\n",
       "      <td>0.754935</td>\n",
       "      <td>0.435659</td>\n",
       "      <td>0.761216</td>\n",
       "      <td>0.433343</td>\n",
       "      <td>0.75</td>\n",
       "      <td>0.437640</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2002-01-01 04:00:00</th>\n",
       "      <td>0.0</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.866025</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.224647e-16</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     is_weekend  sin_24_1  cos_24_1  sin_24_2  cos_24_2  \\\n",
       "date_time                                                                 \n",
       "2002-01-01 00:00:00         0.0  0.000000  1.000000  0.000000  1.000000   \n",
       "2002-01-01 01:00:00         0.0  0.298858  0.931852  0.500000  0.910684   \n",
       "2002-01-01 02:00:00         0.0  0.577350  0.732051  0.866025  0.666667   \n",
       "2002-01-01 03:00:00         0.0  0.816497  0.414214  1.000000  0.333333   \n",
       "2002-01-01 04:00:00         0.0  1.000000  0.000000  0.866025  0.000000   \n",
       "\n",
       "                         sin_24_3  cos_24_3  sin_168_1  cos_168_1  sin_168_2  \\\n",
       "date_time                                                                      \n",
       "2002-01-01 00:00:00  0.000000e+00  1.000000   0.000000   1.000000   0.000000   \n",
       "2002-01-01 01:00:00  7.071068e-01  0.853553   0.250876   0.937391   0.253533   \n",
       "2002-01-01 02:00:00  1.000000e+00  0.500000   0.501402   0.749650   0.505648   \n",
       "2002-01-01 03:00:00  7.071068e-01  0.146447   0.751226   0.437041   0.754935   \n",
       "2002-01-01 04:00:00  1.224647e-16  0.000000   1.000000   0.000000   1.000000   \n",
       "\n",
       "                     cos_168_2  sin_168_3  cos_168_3  \\\n",
       "date_time                                              \n",
       "2002-01-01 00:00:00   1.000000   0.000000   1.000000   \n",
       "2002-01-01 01:00:00   0.937061   0.258052   0.936507   \n",
       "2002-01-01 02:00:00   0.748596   0.512858   0.746826   \n",
       "2002-01-01 03:00:00   0.435659   0.761216   0.433343   \n",
       "2002-01-01 04:00:00   0.000000   1.000000   0.000000   \n",
       "\n",
       "                     time_since_2002-01-01 00:00:00  demand_lag_1  \\\n",
       "date_time                                                           \n",
       "2002-01-01 00:00:00                            0.00      0.817386   \n",
       "2002-01-01 01:00:00                            0.25      0.817386   \n",
       "2002-01-01 02:00:00                            0.50      1.000000   \n",
       "2002-01-01 03:00:00                            0.75      0.437640   \n",
       "2002-01-01 04:00:00                            1.00      0.000000   \n",
       "\n",
       "                     demand_lag_2  demand_lag_3  demand_lag_4  \n",
       "date_time                                                      \n",
       "2002-01-01 00:00:00      0.675273           0.0           0.0  \n",
       "2002-01-01 01:00:00      0.675273           0.0           0.0  \n",
       "2002-01-01 02:00:00      0.675273           0.0           0.0  \n",
       "2002-01-01 03:00:00      1.000000           0.0           0.0  \n",
       "2002-01-01 04:00:00      0.000000           1.0           0.0  "
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pipeline.fit_transform(df.head())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "faf8a062-c2be-4d22-9b1f-73be7f52b4f0",
   "metadata": {},
   "source": [
    "Let's reset our feature engineering pipeline."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "22ad95c0-b937-471c-a2ae-fe17ed2d3f2f",
   "metadata": {},
   "outputs": [],
   "source": [
    "# We can use `clone` to return an unfitted version\n",
    "# of the pipeline.\n",
    "pipeline = clone(pipeline)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d9445dbf-0c67-4e52-9df7-ffc5ff178ef6",
   "metadata": {},
   "source": [
    "Let's build a recursive forecast."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7c79eb0e-d6e1-40eb-a930-80900822f66f",
   "metadata": {},
   "source": [
    "We'll start with configuring the model, the forecast start time, the number of steps to forecast, and the forecasting horizon, and the model."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "3e812426-089d-4add-bbb7-8a630e879efd",
   "metadata": {},
   "outputs": [],
   "source": [
    "from lightgbm import LGBMRegressor\n",
    "from sklearn.linear_model import Lasso, LinearRegression, Ridge"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "fee3871f-b8ca-4063-9272-37c0f71f626a",
   "metadata": {},
   "outputs": [],
   "source": [
    "# --- CONFIG --- #\n",
    "# Define time of first forecast, this determines our train / test split.\n",
    "forecast_start_time = df.index.max() - pd.DateOffset(\n",
    "    weeks=2\n",
    ")  # Start two weeks from the end.\n",
    "\n",
    "# Define number of steps to forecast.\n",
    "num_of_forecast_steps = 24 * 7 * 2\n",
    "\n",
    "# Define the model.\n",
    "model = LinearRegression()\n",
    "\n",
    "# Create a list of periods that we'll forecast over.\n",
    "forecast_horizon = pd.date_range(\n",
    "    forecast_start_time, periods=num_of_forecast_steps, freq=\"H\"\n",
    ")\n",
    "\n",
    "# How much data in the past is needed to create our features\n",
    "look_back_window_size = pd.DateOffset(weeks=1)  # We need the latest 24*7 time periods\n",
    "# in our predict dataframe to build our\n",
    "# window features."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3ffaef60-a54d-4d0c-a19b-e4e5202ec896",
   "metadata": {},
   "source": [
    "Let's create our training dataframe."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "e25af278-6269-4c5f-8c8c-7ff0cd1c01fe",
   "metadata": {},
   "outputs": [],
   "source": [
    "# --- CREATE TRAINING & TESTING DATAFRAME  --- #\n",
    "# Ensure we only have training data up to the start\n",
    "# of the forecast.\n",
    "df_train = df.loc[df.index < forecast_start_time].copy()\n",
    "df_test = df.loc[df.index >= forecast_start_time].copy()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "86ce03ee-d702-4787-b57a-c393bcceeab2",
   "metadata": {},
   "source": [
    "Let's compute our `X_train` and `y_train` and fit our model!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "528ab868-ea31-40cf-aafb-410e29fe9eb3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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      ],
      "text/plain": [
       "LinearRegression()"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# --- FEATURE ENGINEERING--- #\n",
    "# Create X_train and y_train\n",
    "y_train = df_train[target]\n",
    "X_train = pipeline.fit_transform(df_train)\n",
    "\n",
    "# LightGBM cannot handle column names which have\n",
    "# certain characters (e.g., \":\"). We replace these\n",
    "# with `_`.\n",
    "if \"lightgbm\" in model.__module__:  # checks if model is from lightgbm\n",
    "    X_train = X_train.rename(columns=lambda x: re.sub(\"[^A-Za-z0-9_]+\", \"_\", x))\n",
    "\n",
    "\n",
    "# --- MODEL TRAINING---#\n",
    "# Train one-step ahead forecast model\n",
    "model.fit(X_train, y_train)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9bb9e82a-2228-40a7-a73b-9b7a31391cf0",
   "metadata": {},
   "source": [
    "Let's prepare the dataframe that we will pass to `model.predict()`. This will contain some portion of time series during the training period so we can create any features that require historic data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "d80416ff-ee17-4e88-a715-86f2a49fb40e",
   "metadata": {},
   "outputs": [],
   "source": [
    "# --- CREATE DYNAMIC PREDICTION DATAFRAME  --- #\n",
    "# We will recursively append our forecasts to this\n",
    "# dataframe and re-compute our lag and window features from the\n",
    "# target in this dataframe. It contains data in both the training period\n",
    "# and forecast period which is needed for some transformers (e.g., lags and windows).\n",
    "look_back_start_time = forecast_start_time - look_back_window_size\n",
    "\n",
    "# Create `df_predict` which has data going as far back\n",
    "# as needed to create features which need past values.\n",
    "df_predict = df_train.loc[look_back_start_time:].copy()\n",
    "\n",
    "# Extend index into forecast horizon\n",
    "df_predict = pd.concat([df_predict, pd.DataFrame(index=forecast_horizon)])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "65945f51-985d-46e3-a137-21cd2965312e",
   "metadata": {},
   "source": [
    "Let's recursively create `X_test` and make our predictions and append them to the `df_predict` dataframe."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "d629a47f-6f84-4dea-8a53-4e7c4d1fae9c",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "# --- RECURSIVE FORECASTING LOOP --- #\n",
    "for forecast_time in forecast_horizon:\n",
    "    # Compute features during the forecast horizon\n",
    "    X_test = pipeline.transform(df_predict)\n",
    "    X_test = X_test.loc[[forecast_time]]\n",
    "\n",
    "    # Predict one step ahead.\n",
    "    y_pred = model.predict(X_test)\n",
    "\n",
    "    # Append forecast to the target variable columnn in our\n",
    "    # dynamic forecast dataframe `df_predict`. This `df_predict`\n",
    "    # is ready for the next iteration where we will re-compute\n",
    "    # features derived from the target such as lags and windows.\n",
    "    df_predict.loc[[forecast_time], target] = y_pred"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "45b746cd-135f-46b4-8929-4b7e9ecd391d",
   "metadata": {},
   "source": [
    "Let's retrieve our forecast and actuals during the forest horizon."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "7931aa06-0468-41dc-b8a0-43dca249500d",
   "metadata": {},
   "outputs": [],
   "source": [
    "# --- GET FORECAST AND TEST VALUES --- #\n",
    "y_forecast = df_predict.loc[forecast_horizon, target]\n",
    "y_test = df_test.loc[forecast_start_time:, target]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c8c65617-d15a-48ad-b326-faa79c51b2f8",
   "metadata": {},
   "source": [
    "Let's create predictions on the training set using our one step ahead forecast model. This is useful to plot when debugging models."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "3b511c05-ce4e-449d-b849-2ab556d681d5",
   "metadata": {},
   "outputs": [],
   "source": [
    "# --- CREATE IN-SAMPLE PREDICTIONS--- #\n",
    "y_forecast_train = model.predict(X_train)\n",
    "y_forecast_train = pd.DataFrame(y_forecast_train, index=X_train.index, columns=target)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "86ba2671-7108-4a0d-a696-ba88fc844cf1",
   "metadata": {},
   "source": [
    "Let's plot the forecast!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "ca0a3741-e4ec-4811-9e64-ce682b83a30f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Recursive forecast with LinearRegression()')"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# --- PLOTTING --- #\n",
    "# Plot the forecast.\n",
    "fig, ax = plt.subplots(figsize=[12, 7])\n",
    "\n",
    "# Plot training set.\n",
    "y_train.plot(ax=ax, marker=\".\")\n",
    "# Plot actuals in forecasting horizon.\n",
    "y_test.iloc[-24 * 7 * 2 :].plot(ax=ax, marker=\".\", alpha=0.6)\n",
    "# Plot forecast.\n",
    "y_forecast.iloc[-24 * 7 * 2 :].plot(ax=ax)\n",
    "# Plot 1 step forecasts in training data.\n",
    "y_forecast_train.plot(ax=ax)\n",
    "\n",
    "ax.legend([\"train\", \"test\", \"forecast\", \"in-sample forecast\"])\n",
    "ax.set_xlim(xmin=y_train.index.max() - pd.DateOffset(weeks=2))\n",
    "ax.set_xlabel(\"Time\")\n",
    "ax.set_ylabel(f\"{target}\")\n",
    "ax.set_title(f\"Recursive forecast with {model}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b329343e-5055-4a8a-903d-4ec0252239a4",
   "metadata": {},
   "source": [
    "Let's compute the RMSE of this forecast."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "ca4d4411-a247-47cd-882c-bd67833b69f0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1189.484839559471"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Compute error metrics.\n",
    "from sklearn.metrics import mean_squared_error\n",
    "\n",
    "mean_squared_error(\n",
    "    y_true=y_test.loc[y_forecast.index], y_pred=y_forecast, squared=False\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2d649f5f-cfbb-43b8-83d1-b168514acb9b",
   "metadata": {},
   "source": [
    "Feel free to change the dates, try different models, and different features!"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.5"
  },
  "toc": {
   "base_numbering": 1,
   "nav_menu": {},
   "number_sections": true,
   "sideBar": true,
   "skip_h1_title": false,
   "title_cell": "Table of Contents",
   "title_sidebar": "Contents",
   "toc_cell": false,
   "toc_position": {},
   "toc_section_display": true,
   "toc_window_display": false
  },
  "vscode": {
   "interpreter": {
    "hash": "bbdc955b02f52fd4ac17df57dbf42f77a0da462020a5b6d7fea08231d1cd03fe"
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
